{"id":216,"date":"2022-11-28T17:09:08","date_gmt":"2022-11-28T17:09:08","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/?page_id=216"},"modified":"2024-04-26T14:58:24","modified_gmt":"2024-04-26T14:58:24","slug":"exhibitor-workshops","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/agenda\/exhibitor-workshops\/","title":{"rendered":"Exhibitor Workshops"},"content":{"rendered":"<!--themify_builder_content-->\n<div id=\"themify_builder_content-216\" data-postid=\"216\" class=\"themify_builder_content themify_builder_content-216 themify_builder tf_clear\">\n                    <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_5dqo105 tb_first tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_okc4105 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_hvf8106   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Take advantage of these pre-conference workshops for a hands-on demonstration of the latest in Analytics software. All attendees are welcome to join onsite or pre-register. If you\u2019ve already registered for the conference, you can add Exhibitor Workshops by editing your record.<br><br><b>Descriptions and times below:<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_h6e5106 last\">\n                            <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-css_id=\"ots879\" data-lazy=\"1\" class=\"module_row themify_builder_row fullwidth_row_container tb_ots879 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_btuo79 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_yut3830   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Sunday, April 14<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"fico\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-fico tb_c5hs379 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_eh16379 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_roxn259   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>11am-12:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 1<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_dayl379 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_njm8485 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-250x89.png\" width=\"250\" height=\"89\" class=\"wp-post-image wp-image-6050\" title=\"FICO_RGB_Blue (1)\" alt=\"FICO_RGB_Blue (1)\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-250x89.png 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-300x107.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-768x275.png 768w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-200x70.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1.png 1001w\" sizes=\"auto, (max-width: 250px) 100vw, 250px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_iwxd299   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>Global Optimization in FICO\u00ae Xpress and Rapid Application Development and Deployment with FICO\u00ae Xpress Insight<\/h4>\n<p>Presented by:\u00a0Imre P\u00f3lik and Jeff Day<\/p>\n<p>Join us in this workshop to learn about 1) the latest enhancements to the Global optimization solver in FICO\u00ae Xpress, and 2) and how FICO\u00ae Xpress Insight allows you to put the power of your analytical models in the hands of business users in far less time than traditional tools. Speak directly with FICO experts Dr. Imre P\u00f3lik and Dr. Jeff Day at the workshop to learn more!<\/p>\n<p>1. In this talk we are going to present details about the new FICO Xpress Global solver, a new MINLP solver that can handle general nonlinearities (quadratics, trigonometrics, exponentials, powers, etc.) and also any discrete entities supported by Xpress such indicators, special-ordered -sets, semicontinuous variables, etc.). We&#8217;ll discuss the internal workings of the solver, its features and recent performance improvements. We will also talk about use cases for a global vs a local solver.<\/p>\n<p>2. FICO\u00ae Xpress Insight is a rapid application development and deployment framework that integrates with Xpress Solver and your own analytics, enables collaboration across multi-functional teams, and deploys decision support or automated solutions in the cloud or on-premises in far less time than traditional application development tools. We will show how you can rapidly convert Python and Mosel models into complete business applications with Xpress Insight to make your analytical models available to thousands of business users.<\/p>\n<div>This content is most relevant to:<\/div>\n<div>\u00a0<\/div>\n<div>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_ov4d458 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_g4qd458 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_lksq576 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"gams\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-gams tb_k0ep3 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_irhy3 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_kpvp3   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>11am-12:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 2<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_omuo3 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_j9a6682 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-300x120.png\" width=\"300\" height=\"120\" class=\"wp-post-image wp-image-6118\" title=\"GAMS Logo\" alt=\"GAMS Logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-300x120.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-200x80.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo.png 500w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_e2nx454   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>GAMS for Python Users<\/h4>\n<p>Presented by: Atharv Bhosekar<\/p>\n<p>Optimization applications (decision support systems) combine technology and expertise from many different disciplines, including numerical modeling and data science. Python is ubiquitous in data pipelines that instantiate optimization models.<\/p>\n<p>GAMS offers several different Python APIs that enable the efficient integration of GAMS and Python \u2013 merging the power of a specialized algebraic modeling language with a general programming language. These tools enable application builders to leverage the GAMS language where needed while being flexible enough to bend to many different data pipeline architectures.<\/p>\n<ul>\n<li>This session will highlight the entire stack of GAMS\/Python APIs and tools with two primary use-cases in mind: where GAMS is deployed for optimization alongside Python for data-handling and<\/li>\n<li>where a single environment is advantageous, such that the algebraic model is developed and solved within a Python environment.\u00a0<\/li>\n<\/ul>\n<p>Through several real-world examples, we will explore the benefits of GAMS Transfer Python (a data API to exchange data between GAMS and Python) and our new offering GAMSPy. GAMSPy lets you leverage the high-performance GAMS execution system all from a single Python environment.<\/p>\n<div>This content is most relevant to:<\/div>\n<div>\u00a0<\/div>\n<div>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_o3zs66 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_vlpm67 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_bzt667 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"optimizationdirect\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-optimizationdirect tb_45k1303 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_2ftn303 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_o5fc303   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>11am-12:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 3<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_vip2303 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_e0gc69 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-300x103.png\" width=\"300\" height=\"103\" class=\"wp-post-image wp-image-6537\" title=\"Optimization Direct\" alt=\"Optimization Direct\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-300x103.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-768x266.png 768w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-200x69.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct.png 880w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_puoi988   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>How to Deploy applications that combine machine learning\/deep learning tools and optimization technologies such as XPRESS\/ ODH|XPRESS<\/h4>\n<p>Presented by: Robert Ashford<\/p>\n<p>Organizations are increasingly hiring Data Scientists with Open Source skills. They leverage the capabilities and work with Open Source tools like R, Python, Spark, as well as integration with FICO-XPRESS and large data. Come learn how to integrate with Open Source tools to enable clients to get the best of both worlds (Open Source programming and the Modeler GUIs for those who prefer not to code). Furthermore, we will review the latest developments\/results in FICO-XPRESS and the new ODH|XPRESS.<\/p>\n<div>This content is most relevant to:<\/div>\n<div>\u00a0<\/div>\n<div>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_jetl290 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_ie2y290 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_m6rb290 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"hexaly\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-hexaly tb_h247844 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_r2kg845 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_d4k6845   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>1-2:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 3<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_c8i3845 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_44bw845 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-300x96.png\" width=\"300\" height=\"96\" class=\"wp-post-image wp-image-5158\" title=\"hexaly-orange\" alt=\"hexaly-orange\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-300x96.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-200x65.png 200w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_bivm845   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>Hexaly, a New Kind of Global Optimization Solver<\/h4>\n<p>Presented by: Frederic Gardi<\/p>\n<div>\u00a0<\/div>\n<div>Hexaly Optimizer is a new kind of global optimization solver. Its modeling interface is nonlinear and set-oriented. It also supports user-coded functions, thus enabling black-box optimization and, more particularly, simulation optimization. In a sense, Hexaly APIs unify modeling concepts from mixed-linear programming, nonlinear programming, and constraint programming. Under the hood, Hexaly combines various exact and heuristic optimization methods: spatial branch-and-bound, simplex methods, interior-point methods, augmented Lagrangian methods, automatic Dantzig-Wolfe reformulation, column and row generation, propagation methods, local search, direct search, population-based methods, and surrogate modeling techniques for black-box optimization.<\/div>\n<div>\u00a0<\/div>\n<div>Regarding performance benchmarks, Hexaly distinguishes itself against the leading solvers in the market, like Gurobi, IBM Cplex, and Google OR Tools, by delivering fast and scalable solutions to problems in the spaces of Supply Chain and Workforce Management like Routing, Scheduling, Packing, Clustering, and Location. For example, on notoriously hard problems like the Pickup and Delivery Problem with Time Windows or Flexible Job Shop Scheduling with Setup Times, Hexaly delivers solutions with a gap to the best solutions known in the literature smaller than 1% in a few minutes of running times on a basic computer.<\/div>\n<div><br>In addition to the Optimizer, we provide an innovative development platform called Hexaly Studio to model and solve rich Vehicle Routing and Job Shop Scheduling problems in a no-code fashion. The user can define its problem and data, run the Optimizer, visualize the solutions and key metrics through dashboards, and deploy the resulting app in the cloud \u2013 without coding. This web-based platform is particularly interesting for educational purposes; it is free for faculty and students.<\/div>\n<div>\u00a0<\/div>\n<div>This content is most relevant to:<\/div>\n<div>\u00a0<\/div>\n<div>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_zq0e646 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_yigs647 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_7eye647 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"jmp\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-jmp tb_yxlf715 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_n8mv715 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_eo34715   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>1-2:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 4<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_i5f4715 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_vhzn523 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-300x82.png\" width=\"300\" height=\"82\" class=\"wp-post-image wp-image-6037\" title=\"JMP logo\" alt=\"JMP logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-300x82.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-200x54.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo.png 557w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_rx5x715   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>Predictive Modeling with Interactive, No-Code Desktop Software<\/h4>\n<p>Presented by: Ross Metusalem<\/p>\n<p>JMP Pro is no-code desktop software for data visualization, statistical analysis, and machine learning. Its combination of an easy-to-use, interactive interface and powerful analytical capabilities makes advanced predictive modeling accessible to practitioners of all skill levels, from students to industry pros.<\/p>\n<p>This workshop presents the end-to-end predictive modeling workflow in JMP Pro via a case study in predicting home equity loan defaults. We&#8217;ll begin by summarizing and exploring our training data set using interactive graphics and statistical summaries. We&#8217;ll next utilize JMP Pro&#8217;s Model Screening platform to efficiently fit and compare multiple candidate models, including neural nets and decision trees. We&#8217;ll then perform model tuning and cross-validation to arrive at a final model, interactively explore decision thresholds for scoring new loan applications, and finally export the model to be deployed outside of JMP Pro.<\/p>\n<p>The content you are presenting is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_6dpf124 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_mph0124 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_1gui124 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"nextmv\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-nextmv tb_fh5i874 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_1vqt875 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_awmq875   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>1-2:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 1<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_lgp2875 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_d29z893 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-299x74.png\" width=\"299\" height=\"74\" class=\"wp-post-image wp-image-4627\" title=\"nextmv-logo-horizo\" alt=\"nextmv-logo-horizo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-299x74.png 299w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-300x75.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-200x50.png 200w\" sizes=\"auto, (max-width: 299px) 100vw, 299px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_odrh678   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>The Sushi is Ready. How do I Deliver It? Forecast, Schedule, Route with DecisionOps<\/h4>\n<p>Presented by: Ryan O&#8217;Neil and Nicole Misek<\/p>\n<p>Countless logistics decisions happen every day for food delivery apps, healthcare scheduling systems, subscription box services, and beyond. Building the models to power said decision making is well practiced. Standing up, managing, and scaling the infrastructure, tooling, and teams that support those models is usually a bespoke practice (if performed at all) and is often what stands in the way of a model\u2019s real-world impact. But it doesn\u2019t have to be.\u00a0<\/p>\n<p>This hands-on session looks at the story of a sushi roll order, the logistics models (demand forecasting, scheduling, and routing) involved, and the DecisionOps tooling (testing, CI\/CD, model management, collaboration) that makes delivering your objectives so much easier than it\u2019s ever been before.\u00a0<\/p>\n<p>Join us to explore accelerating the impact of models built with OR-Tools, Pyomo, HiGHS, Nextroute, and more.<\/p>\n<p>This content is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_trgu936 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_rp92936 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_88o3936 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"princetonconsultants\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-princetonconsultants tb_bzpu19 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_g86z19 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_uouo19   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Time:<br><b>1-2:45pm<\/b><\/p>\n<p>Location:<br><b>Windsong 2<\/b><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_dxcs19 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_91ei458 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-300x120.jpg\" width=\"300\" height=\"120\" class=\"wp-post-image wp-image-5010\" title=\"Princeton_Consultants\" alt=\"Princeton_Consultants\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-300x120.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-200x80.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants.jpg 400w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_m0k2364   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>pandas for Analytics Practitioners, with Applications in Optimization<\/h4>\n<p>Presented by: Irv Lustig, PhD<\/p>\n<p>The Python library pandas (<a href=\"http:\/\/pandas.pydata.org\/\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"622fa93bb0ebf976bd76e19a\">http:\/\/pandas.pydata.org\/<\/a>) is popular with data scientists, who use it to carry out an entire data analysis workflow in Python. When building analytics models, we often work with data in tables that are sourced from databases, CSV files, and spreadsheets. pandas provides a uniform environment for working with data tables with a large number of methods for manipulating tabular data, many of which are directly applicable for building large scale optimization models. In this workshop, Irv Lustig will present an introduction to pandas and illustrate some of its powerful features that can accelerate optimization model development and deployment.<\/p>\n<p>This content is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"ampl\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-ampl tb_car9612 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_kl8g612 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_luzi612   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p>\n<p style=\"color: rgb(32, 34, 37); font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 2<\/b><\/p>\n<div>\n<div>&nbsp;<\/div>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_n7ri612 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_917e639 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-300x90.png\" width=\"300\" height=\"90\" class=\"wp-post-image wp-image-6485\" title=\"ampl_logo_inline_color\" alt=\"ampl_logo_inline_color\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-300x90.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-205x63.png 205w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-200x59.png 200w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_rwv594   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>\u00a0<\/h4>\n<h4>\u00a0<\/h4>\n<h4>Prescriptive Analytics from Model to App: Learn how you can build optimization applications quickly and reliably, with AMPL, Python, Streamlit &#8212; and AI<\/h4>\n<p>Presented by: Bob Fourer, Filipe Brandao, and Gyorgy Matyasfalvi<\/p>\n<table width=\"100%\">\n<tbody>\n<tr>\n<td>\n<p>Optimization is the most widely adopted technology of Prescriptive Analytics, but also the most\u00a0challenging to implement. This presentation takes you through the steps of a proven approach that combines the best features of two implementation environments:<\/p>\n<ul>\n<li>Model development in AMPL, a language and system designed for the needs of formulating and\u00a0validating optimization models.<\/li>\n<li>Application building in Python, the most popular environment for building Analytics models into\u00a0deployable applications.<\/li>\n<\/ul>\n<p>You\u2019ll also see how new AI technology is enabling a rapid development process for both AMPL and Python, reducing the time and effort to produce a working application that\u2019s ready for end-users. <br><br>We begin by introducing model-based optimization, the key approach to streamlining the optimization modeling cycle and building successful applications today. Using AMPL\u2019s natural modeling language, you formulate optimization problems more like you think about them, while AMPL\u2019s customized solver interfaces automate the often-complicated reformulations required by advanced solver algorithms. <br><br>Our presentation next shows how AMPL and Python work together for building optimization into\u00a0enterprise systems. AMPL integrates with Python through the \u201camplpy\u201d package, allowing for smooth data interchange between Python data structures, Pandas dataframes, and AMPL models. In contrast to Python-only modeling solutions, amplpy leverages AMPL\u2019s straightforward model formulation and efficient model processing, while maintaining access to Python\u2019s vast ecosystem for data preparation, solution analysis, and visualization. <br><br>The workshop concludes with a rapid deployment demonstration, bringing together AMPL, Python, and AI. Our example features generative AI\u2019s ability to produce both AMPL models and Python programs, and Streamlit\u2019s features for turning Python scripts into shareable web apps.<\/p>\n<p>This content is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_0ah8117 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_tdlq118 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_utrl118 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"chiaha\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-chiaha tb_yfqc325 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_5qrf326 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_oiy2326   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p>\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 4<\/b><\/p>\n<div>\n<div>\u00a0<\/div>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_2hzu326 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_eqmw810 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-200x186.jpg\" width=\"200\" height=\"186\" class=\"wp-post-image wp-image-6392\" title=\"ChiAha web_ready_company_logo\" alt=\"ChiAha web_ready_company_logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-200x186.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-300x280.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo.jpg 590w\" sizes=\"auto, (max-width: 200px) 100vw, 200px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_7euz119   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>Learn how ChiAha can help you accelerate your journey from raw data to prediction!<\/h4>\n<p>Presented by: Andrew Siprelle<\/p>\n<div>\u00a0<\/div>\n<div>ChiAha is a powerful hybrid of simulation, optimization, and machine learning designed to help optimize production in high-speed, high-volume production.\u00a0In this workshop, we will outline the journey that led to the creation of our revolutionary new engine and associated tools.<\/div>\n<div>\u00a0<\/div>\n<div>This content is most relevant to:<\/div>\n<div>\n<p>\u00a0<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_yjk1631 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_y1o7631 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_6ebi631 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"gurobi\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-gurobi tb_53ss169 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_ycu4251 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_0zjy509   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p>\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 1<\/b><\/p>\n<div>\n<div>\u00a0<\/div>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_3vvj169 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_r3bz643 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-300x79.png\" width=\"300\" height=\"79\" class=\"wp-post-image wp-image-4926\" title=\"Gurobi web_ready_company_logo\" alt=\"Gurobi web_ready_company_logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-300x78.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-350x92.png 350w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-200x52.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-250x66.png 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo.png 436w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_5x5e458   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>Gurobi 11.0 \u2013 Helping You to Build, Solve, and Deploy Optimization Models<\/h4>\n<p>Presented by: Xavier Nodet, Dan Jeffrey, Jue Xue, and Irv Lustig<\/p>\n<p class=\"MsoNormal\">In this workshop, attendees will get a look at our latest product release, Gurobi 11.0\u2014including exciting performance improvements to Gurobi\u2019s core algorithms. We\u2019ll do a walkthrough of Gurobi\u2019s new Mixed-Integer Nonlinear Programming (MINLP) capabilities and highlight features that make the model-building and solving process easier.<span style=\"font-family: 'Arial',sans-serif;\">\u200b<\/span><\/p>\n<p><span style=\"font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Aptos; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\">In the second half of the workshop, we will show a preview of our new price optimization demo. We will also have special guest Irv Lustig, Optimization Principal at Princeton Consultants, join us and illustrate best practices for using pandas with Gurobi via examples. Don\u2019t miss this special workshop!<\/span><\/p>\n<p>This content is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>\n    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_owa4252 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_gvr0253 first\">\n                    <!-- module divider -->\n<div  class=\"module tf_mw module-divider tb_nise253 solid   \" style=\"border-width: 1px;border-color: #202225;margin-bottom: 12px;\" data-lazy=\"1\">\n    <\/div>\n<!-- \/module divider -->\n        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"sas\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-sas tb_jlw671 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_sph671 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_opxa71   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p>\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 3<\/b><\/p>\n<div>\n<div>\u00a0<\/div>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_5p7i71 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_1y26141 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-250x102.jpg\" width=\"250\" height=\"102\" class=\"wp-post-image wp-image-5349\" title=\"sas-logo-blue\" alt=\"sas-logo-blue\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-250x103.jpg 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-300x124.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-200x81.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue.jpg 600w\" sizes=\"auto, (max-width: 250px) 100vw, 250px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image --><!-- module text -->\n<div  class=\"module module-text tb_xjf4147   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h4>SAS Analytics and Customized Optimization Solutions<\/h4>\n<p>Presented by: Rob Pratt and Subramanian Pazhani<\/p>\n<p>SAS offers extensive analytic capabilities, including machine learning, deep learning, natural language processing, statistical analysis, optimization, and simulation. SAS analytic functionality is also available through the open, cloud-enabled design of SAS\u00ae Viya\u00ae.\u00a0 You can program in SAS or in other languages \u2013 Python, Lua, Java, and R. SAS Analytics is equipped with AI-enabled automations and modern low-code or no-code user interfaces that democratize data science usage in your organization and offer unparalleled speed to value.<\/p>\n<p>\u00a0<span style=\"background-color: initial; font-size: 1em;\">We will first review the SAS analytics portfolio, then highlight recently added optimization features, and finally explore case studies in optimization, focusing on custom-built solutions that combine heuristics with optimization algorithms. Complex business problems typically need advanced analytics tools and solutions to efficiently solve them, with flexibility to create analytics pipelines that use complementary solution techniques. We will discuss customer business problems and share how to use SAS multi-stage analytics solution approaches. During the discussion, we will highlight the capabilities and flexibility of SAS in seamlessly implementing these multi-stage custom-built optimization solutions. We will conclude with an overview of SAS customer outcomes from various analytics projects.<\/span><\/p>\n<p>This content is most relevant to:<\/p>\n<ul>\n<li>Associate (Early Career)<\/li>\n<li>Professional (Mid-Career)<\/li>\n<li>Executive (Senior Level)<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n        <\/div>\n<!--\/themify_builder_content-->","protected":false},"excerpt":{"rendered":"<p>Take advantage of these pre-conference workshops for a hands-on demonstration of the latest in Analytics software. All attendees are welcome to join onsite or pre-register. If you\u2019ve already registered for the conference, you can add Exhibitor Workshops by editing your record.Descriptions and times below:<\/p>\n","protected":false},"author":1001137,"featured_media":0,"parent":1208,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-216","page","type-page","status-publish","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.0 (Yoast SEO v26.0) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Exhibitor Workshops - 2024 INFORMS Analytics Conference<\/title>\n<meta name=\"description\" content=\"Take advantage of these pre-conference workshops for a hands on demonstration of the latest in analytics software.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/agenda\/exhibitor-workshops\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Exhibitor Workshops\" \/>\n<meta property=\"og:description\" content=\"Take advantage of these pre-conference workshops for a hands on demonstration of the latest in analytics software.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/agenda\/exhibitor-workshops\/\" \/>\n<meta property=\"og:site_name\" content=\"2024 INFORMS Analytics Conference\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/INFORMSpage\/\" \/>\n<meta property=\"article:modified_time\" content=\"2024-04-26T14:58:24+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2023\/11\/analytics-2024-logo.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"414\" \/>\n\t<meta property=\"og:image:height\" content=\"414\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@2023_Analytics\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/agenda\/exhibitor-workshops\/\",\"url\":\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/agenda\/exhibitor-workshops\/\",\"name\":\"Exhibitor Workshops - 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All attendees are welcome to join onsite or pre-register. If you\u2019ve already registered for the conference, you can add Exhibitor Workshops by editing your record.<br><br><b>Descriptions and times below:<\/b><\/p>\n<p>Sunday, April 14<\/p>\n<p>Time:<br><b>11am-12:45pm<\/b><\/p> <p>Location:<br><b>Windsong 1<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-250x89.png\" width=\"250\" height=\"89\" title=\"FICO_RGB_Blue (1)\" alt=\"FICO_RGB_Blue (1)\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-250x89.png 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-300x107.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-768x275.png 768w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1-200x70.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/FICO_RGB_Blue-1.png 1001w\" sizes=\"(max-width: 250px) 100vw, 250px\" \/>\n<h4>Global Optimization in FICO\u00ae Xpress and Rapid Application Development and Deployment with FICO\u00ae Xpress Insight<\/h4> <p>Presented by:\u00a0Imre P\u00f3lik and Jeff Day<\/p> <p>Join us in this workshop to learn about 1) the latest enhancements to the Global optimization solver in FICO\u00ae Xpress, and 2) and how FICO\u00ae Xpress Insight allows you to put the power of your analytical models in the hands of business users in far less time than traditional tools. Speak directly with FICO experts Dr. Imre P\u00f3lik and Dr. Jeff Day at the workshop to learn more!<\/p> <p>1. In this talk we are going to present details about the new FICO Xpress Global solver, a new MINLP solver that can handle general nonlinearities (quadratics, trigonometrics, exponentials, powers, etc.) and also any discrete entities supported by Xpress such indicators, special-ordered -sets, semicontinuous variables, etc.). We'll discuss the internal workings of the solver, its features and recent performance improvements. We will also talk about use cases for a global vs a local solver.<\/p> <p>2. FICO\u00ae Xpress Insight is a rapid application development and deployment framework that integrates with Xpress Solver and your own analytics, enables collaboration across multi-functional teams, and deploys decision support or automated solutions in the cloud or on-premises in far less time than traditional application development tools. We will show how you can rapidly convert Python and Mosel models into complete business applications with Xpress Insight to make your analytical models available to thousands of business users.<\/p> This content is most relevant to: \u00a0\n<ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p>Time:<br><b>11am-12:45pm<\/b><\/p> <p>Location:<br><b>Windsong 2<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-300x120.png\" width=\"300\" height=\"120\" title=\"GAMS Logo\" alt=\"GAMS Logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-300x120.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo-200x80.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/GAMS-Logo.png 500w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>GAMS for Python Users<\/h4> <p>Presented by: Atharv Bhosekar<\/p> <p>Optimization applications (decision support systems) combine technology and expertise from many different disciplines, including numerical modeling and data science. Python is ubiquitous in data pipelines that instantiate optimization models.<\/p> <p>GAMS offers several different Python APIs that enable the efficient integration of GAMS and Python \u2013 merging the power of a specialized algebraic modeling language with a general programming language. These tools enable application builders to leverage the GAMS language where needed while being flexible enough to bend to many different data pipeline architectures.<\/p> <ul> <li>This session will highlight the entire stack of GAMS\/Python APIs and tools with two primary use-cases in mind: where GAMS is deployed for optimization alongside Python for data-handling and<\/li> <li>where a single environment is advantageous, such that the algebraic model is developed and solved within a Python environment.\u00a0<\/li> <\/ul> <p>Through several real-world examples, we will explore the benefits of GAMS Transfer Python (a data API to exchange data between GAMS and Python) and our new offering GAMSPy. GAMSPy lets you leverage the high-performance GAMS execution system all from a single Python environment.<\/p> This content is most relevant to: \u00a0\n<ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p>Time:<br><b>11am-12:45pm<\/b><\/p> <p>Location:<br><b>Windsong 3<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-300x103.png\" width=\"300\" height=\"103\" title=\"Optimization Direct\" alt=\"Optimization Direct\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-300x103.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-768x266.png 768w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct-200x69.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/Optimization-Direct.png 880w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>How to Deploy applications that combine machine learning\/deep learning tools and optimization technologies such as XPRESS\/ ODH|XPRESS<\/h4> <p>Presented by: Robert Ashford<\/p> <p>Organizations are increasingly hiring Data Scientists with Open Source skills. They leverage the capabilities and work with Open Source tools like R, Python, Spark, as well as integration with FICO-XPRESS and large data. Come learn how to integrate with Open Source tools to enable clients to get the best of both worlds (Open Source programming and the Modeler GUIs for those who prefer not to code). Furthermore, we will review the latest developments\/results in FICO-XPRESS and the new ODH|XPRESS.<\/p> This content is most relevant to: \u00a0\n<ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p>Time:<br><b>1-2:45pm<\/b><\/p> <p>Location:<br><b>Windsong 3<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-300x96.png\" width=\"300\" height=\"96\" title=\"hexaly-orange\" alt=\"hexaly-orange\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-300x96.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/hexaly-orange-200x65.png 200w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>Hexaly, a New Kind of Global Optimization Solver<\/h4> <p>Presented by: Frederic Gardi<\/p> \u00a0 Hexaly Optimizer is a new kind of global optimization solver. Its modeling interface is nonlinear and set-oriented. It also supports user-coded functions, thus enabling black-box optimization and, more particularly, simulation optimization. In a sense, Hexaly APIs unify modeling concepts from mixed-linear programming, nonlinear programming, and constraint programming. Under the hood, Hexaly combines various exact and heuristic optimization methods: spatial branch-and-bound, simplex methods, interior-point methods, augmented Lagrangian methods, automatic Dantzig-Wolfe reformulation, column and row generation, propagation methods, local search, direct search, population-based methods, and surrogate modeling techniques for black-box optimization. \u00a0 Regarding performance benchmarks, Hexaly distinguishes itself against the leading solvers in the market, like Gurobi, IBM Cplex, and Google OR Tools, by delivering fast and scalable solutions to problems in the spaces of Supply Chain and Workforce Management like Routing, Scheduling, Packing, Clustering, and Location. For example, on notoriously hard problems like the Pickup and Delivery Problem with Time Windows or Flexible Job Shop Scheduling with Setup Times, Hexaly delivers solutions with a gap to the best solutions known in the literature smaller than 1% in a few minutes of running times on a basic computer. <br>In addition to the Optimizer, we provide an innovative development platform called Hexaly Studio to model and solve rich Vehicle Routing and Job Shop Scheduling problems in a no-code fashion. The user can define its problem and data, run the Optimizer, visualize the solutions and key metrics through dashboards, and deploy the resulting app in the cloud \u2013 without coding. This web-based platform is particularly interesting for educational purposes; it is free for faculty and students. \u00a0 This content is most relevant to: \u00a0\n<ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p>Time:<br><b>1-2:45pm<\/b><\/p> <p>Location:<br><b>Windsong 4<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-300x82.png\" width=\"300\" height=\"82\" title=\"JMP logo\" alt=\"JMP logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-300x82.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo-200x54.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/JMP-logo.png 557w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>Predictive Modeling with Interactive, No-Code Desktop Software<\/h4> <p>Presented by: Ross Metusalem<\/p> <p>JMP Pro is no-code desktop software for data visualization, statistical analysis, and machine learning. Its combination of an easy-to-use, interactive interface and powerful analytical capabilities makes advanced predictive modeling accessible to practitioners of all skill levels, from students to industry pros.<\/p> <p>This workshop presents the end-to-end predictive modeling workflow in JMP Pro via a case study in predicting home equity loan defaults. We'll begin by summarizing and exploring our training data set using interactive graphics and statistical summaries. We'll next utilize JMP Pro's Model Screening platform to efficiently fit and compare multiple candidate models, including neural nets and decision trees. We'll then perform model tuning and cross-validation to arrive at a final model, interactively explore decision thresholds for scoring new loan applications, and finally export the model to be deployed outside of JMP Pro.<\/p> <p>The content you are presenting is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <\/ul>\n\n<p>Time:<br><b>1-2:45pm<\/b><\/p> <p>Location:<br><b>Windsong 1<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-299x74.png\" width=\"299\" height=\"74\" title=\"nextmv-logo-horizo\" alt=\"nextmv-logo-horizo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-299x74.png 299w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-300x75.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/nextmv-logo-horizo-200x50.png 200w\" sizes=\"(max-width: 299px) 100vw, 299px\" \/>\n<h4>The Sushi is Ready. How do I Deliver It? Forecast, Schedule, Route with DecisionOps<\/h4> <p>Presented by: Ryan O'Neil and Nicole Misek<\/p> <p>Countless logistics decisions happen every day for food delivery apps, healthcare scheduling systems, subscription box services, and beyond. Building the models to power said decision making is well practiced. Standing up, managing, and scaling the infrastructure, tooling, and teams that support those models is usually a bespoke practice (if performed at all) and is often what stands in the way of a model\u2019s real-world impact. But it doesn\u2019t have to be.\u00a0<\/p> <p>This hands-on session looks at the story of a sushi roll order, the logistics models (demand forecasting, scheduling, and routing) involved, and the DecisionOps tooling (testing, CI\/CD, model management, collaboration) that makes delivering your objectives so much easier than it\u2019s ever been before.\u00a0<\/p> <p>Join us to explore accelerating the impact of models built with OR-Tools, Pyomo, HiGHS, Nextroute, and more.<\/p> <p>This content is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p>Time:<br><b>1-2:45pm<\/b><\/p> <p>Location:<br><b>Windsong 2<\/b><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-300x120.jpg\" width=\"300\" height=\"120\" title=\"Princeton_Consultants\" alt=\"Princeton_Consultants\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-300x120.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants-200x80.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Princeton_Consultants.jpg 400w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>pandas for Analytics Practitioners, with Applications in Optimization<\/h4> <p>Presented by: Irv Lustig, PhD<\/p> <p>The Python library pandas (<a href=\"http:\/\/pandas.pydata.org\/\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"622fa93bb0ebf976bd76e19a\">http:\/\/pandas.pydata.org\/<\/a>) is popular with data scientists, who use it to carry out an entire data analysis workflow in Python. When building analytics models, we often work with data in tables that are sourced from databases, CSV files, and spreadsheets. pandas provides a uniform environment for working with data tables with a large number of methods for manipulating tabular data, many of which are directly applicable for building large scale optimization models. In this workshop, Irv Lustig will present an introduction to pandas and illustrate some of its powerful features that can accelerate optimization model development and deployment.<\/p> <p>This content is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p> <p style=\"color: rgb(32, 34, 37); font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 2<\/b><\/p>\n&nbsp;\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-300x90.png\" width=\"300\" height=\"90\" title=\"ampl_logo_inline_color\" alt=\"ampl_logo_inline_color\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-300x90.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-205x63.png 205w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ampl_logo_inline_color-200x59.png 200w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>\u00a0<\/h4> <h4>\u00a0<\/h4> <h4>Prescriptive Analytics from Model to App: Learn how you can build optimization applications quickly and reliably, with AMPL, Python, Streamlit -- and AI<\/h4> <p>Presented by: Bob Fourer, Filipe Brandao, and Gyorgy Matyasfalvi<\/p> <table width=\"100%\"> <tbody> <tr> <td> <p>Optimization is the most widely adopted technology of Prescriptive Analytics, but also the most\u00a0challenging to implement. This presentation takes you through the steps of a proven approach that combines the best features of two implementation environments:<\/p> <ul> <li>Model development in AMPL, a language and system designed for the needs of formulating and\u00a0validating optimization models.<\/li> <li>Application building in Python, the most popular environment for building Analytics models into\u00a0deployable applications.<\/li> <\/ul> <p>You\u2019ll also see how new AI technology is enabling a rapid development process for both AMPL and Python, reducing the time and effort to produce a working application that\u2019s ready for end-users. <br><br>We begin by introducing model-based optimization, the key approach to streamlining the optimization modeling cycle and building successful applications today. Using AMPL\u2019s natural modeling language, you formulate optimization problems more like you think about them, while AMPL\u2019s customized solver interfaces automate the often-complicated reformulations required by advanced solver algorithms. <br><br>Our presentation next shows how AMPL and Python work together for building optimization into\u00a0enterprise systems. AMPL integrates with Python through the \u201camplpy\u201d package, allowing for smooth data interchange between Python data structures, Pandas dataframes, and AMPL models. In contrast to Python-only modeling solutions, amplpy leverages AMPL\u2019s straightforward model formulation and efficient model processing, while maintaining access to Python\u2019s vast ecosystem for data preparation, solution analysis, and visualization. <br><br>The workshop concludes with a rapid deployment demonstration, bringing together AMPL, Python, and AI. Our example features generative AI\u2019s ability to produce both AMPL models and Python programs, and Streamlit\u2019s features for turning Python scripts into shareable web apps.<\/p> <p>This content is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul> <\/td> <\/tr> <\/tbody> <\/table>\n\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p> <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 4<\/b><\/p>\n\u00a0\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-200x186.jpg\" width=\"200\" height=\"186\" title=\"ChiAha web_ready_company_logo\" alt=\"ChiAha web_ready_company_logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-200x186.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo-300x280.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/03\/ChiAha-web_ready_company_logo.jpg 590w\" sizes=\"(max-width: 200px) 100vw, 200px\" \/>\n<h4>Learn how ChiAha can help you accelerate your journey from raw data to prediction!<\/h4> <p>Presented by: Andrew Siprelle<\/p> \u00a0 ChiAha is a powerful hybrid of simulation, optimization, and machine learning designed to help optimize production in high-speed, high-volume production.\u00a0In this workshop, we will outline the journey that led to the creation of our revolutionary new engine and associated tools. \u00a0 This content is most relevant to:\n<p>\u00a0<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p> <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 1<\/b><\/p>\n\u00a0\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-300x79.png\" width=\"300\" height=\"79\" title=\"Gurobi web_ready_company_logo\" alt=\"Gurobi web_ready_company_logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-300x78.png 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-350x92.png 350w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-200x52.png 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo-250x66.png 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Gurobi-web_ready_company_logo.png 436w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\n<h4>Gurobi 11.0 \u2013 Helping You to Build, Solve, and Deploy Optimization Models<\/h4> <p>Presented by: Xavier Nodet, Dan Jeffrey, Jue Xue, and Irv Lustig<\/p> <p>In this workshop, attendees will get a look at our latest product release, Gurobi 11.0\u2014including exciting performance improvements to Gurobi\u2019s core algorithms. We\u2019ll do a walkthrough of Gurobi\u2019s new Mixed-Integer Nonlinear Programming (MINLP) capabilities and highlight features that make the model-building and solving process easier.\u200b<\/p> <p>In the second half of the workshop, we will show a preview of our new price optimization demo. We will also have special guest Irv Lustig, Optimization Principal at Princeton Consultants, join us and illustrate best practices for using pandas with Gurobi via examples. Don\u2019t miss this special workshop!<\/p> <p>This content is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n\n<p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Time:<br><b style=\"background-color: initial;\">3-4:45pm<\/b><\/p> <p style=\"color: #202225; font-size: 16px; letter-spacing: normal;\">Location:<br><b>Windsong 3<\/b><\/p>\n\u00a0\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-250x102.jpg\" width=\"250\" height=\"102\" title=\"sas-logo-blue\" alt=\"sas-logo-blue\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-250x103.jpg 250w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-300x124.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue-200x81.jpg 200w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/sas-logo-blue.jpg 600w\" sizes=\"(max-width: 250px) 100vw, 250px\" \/>\n<h4>SAS Analytics and Customized Optimization Solutions<\/h4> <p>Presented by: Rob Pratt and Subramanian Pazhani<\/p> <p>SAS offers extensive analytic capabilities, including machine learning, deep learning, natural language processing, statistical analysis, optimization, and simulation. SAS analytic functionality is also available through the open, cloud-enabled design of SAS\u00ae Viya\u00ae.\u00a0 You can program in SAS or in other languages \u2013 Python, Lua, Java, and R. SAS Analytics is equipped with AI-enabled automations and modern low-code or no-code user interfaces that democratize data science usage in your organization and offer unparalleled speed to value.<\/p> <p>\u00a0We will first review the SAS analytics portfolio, then highlight recently added optimization features, and finally explore case studies in optimization, focusing on custom-built solutions that combine heuristics with optimization algorithms. Complex business problems typically need advanced analytics tools and solutions to efficiently solve them, with flexibility to create analytics pipelines that use complementary solution techniques. We will discuss customer business problems and share how to use SAS multi-stage analytics solution approaches. During the discussion, we will highlight the capabilities and flexibility of SAS in seamlessly implementing these multi-stage custom-built optimization solutions. We will conclude with an overview of SAS customer outcomes from various analytics projects.<\/p> <p>This content is most relevant to:<\/p> <ul> <li>Associate (Early Career)<\/li> <li>Professional (Mid-Career)<\/li> <li>Executive (Senior Level)<\/li> <\/ul>\n","_links":{"self":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/pages\/216","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/users\/1001137"}],"replies":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/comments?post=216"}],"version-history":[{"count":323,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/pages\/216\/revisions"}],"predecessor-version":[{"id":7025,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/pages\/216\/revisions\/7025"}],"up":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/pages\/1208"}],"wp:attachment":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/wp-json\/wp\/v2\/media?parent=216"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}