Advanced Tutorials

Track Coordinators: Henry Lam (Columbia University), Giulia Pedrielli (Arizona State University)

The Advanced Tutorial track is oriented toward experienced practitioners and researchers who want to hear about the most recent developments, presented in a directly applicable form. The track encourages tutorials that focus on topics of special interest, as well as the latest theory and methods and resulting modeling, simulation, and analysis tools. Also of interest are pertinent topics in related disciplines, such as social network, healthcare, epidemic disease, energy, emergency response, augmented and virtual reality, simulation of big-data, blockchain, and so on. These special-focus sessions give practitioners and researchers a survey of recent fundamental advances in the discipline of modeling and simulation.

Agent-Based Simulation

Track Coordinators: Chris Kuhlman (University of Virginia), Andrew Collins (Old Dominion University)

The Agent-Based Simulation (ABS) track is interested in theoretical, methodological and applied research that involves synergistic interaction between simulation and agent technologies. It covers multi-agent systems, agent-based simulation and agent-directed simulation. Contributions to the ABS track can be advancements of agent-based simulation modeling and/or analysis, studies of complex adaptive systems or self-organizing emergent phenomena using agent-based models, and applications of ABS to fields such as natural sciences, business and management, health and social care, engineering, environmental science, social sciences, humanities, arts, and intelligent transportation systems. Also, of interest are contributions that demonstrate the use of agents as support facilities to enable computer assistance in simulation-based problem solving (i.e., agent-supported simulation), or the use of agents for the generation of model behavior in a simulation study. Topics include, but are not limited to, the following:

Theory and Methodologies:

  • High-level specification or modeling languages for agent-based simulation
  • Advanced execution platforms for agent-based simulation (e.g. cloud, edge computing)
  • Formal models of agents and agent societies
  • Verification, validation, testing; quality assurance; as well as failure avoidance in agent-based simulations
  • Experiments and output analysis of agent-based simulations
  • Advanced agent features for agent-directed simulation: e.g., agent-based simulation to monitor multi- simulation studies, agents in design and monitoring of simulation experiments and analysis of results
  • Interface with artificial intelligence and analytics
  • Incorporating big-data into agent-based models


  • Autonomous and adaptive systems
  • Complex adaptive systems modeling
  • Self-organizing systems
  • Applications in business or management (e.g. operations, supply chain, marketing, finance)
  • Applications in physical science and engineering (e.g. environment, biomedical, engineering)
  • Applications in social sciences, humanities, and arts
  • Simulation modeling of agent technologies at the organization, interaction (e.g., communication, negotiation, coordination, collaboration) and agent level (e.g., deliberation, social agents, computational autonomy)

Analysis Methodology

Track Coordinators: Ben Feng (University of Waterloo), Sara Shashaani (North Carolina State University)

The Analysis Methodology track is intended to cover a variety of empirical, computational, mathematical and statistical techniques in the context of their application to simulation analysis. The focus is on analysis methods for simulation input and output. Papers covering the construction and calibration of simulation inputs that either improve upon standard approaches or introduce new methods are encouraged. Papers that deal with the general efficiency, accuracy and appropriateness of a simulation are also covered by the Analysis Methodology track. We also welcome suggestions for sessions on emerging topics related to, but not limited to, the following:

  • Simulation methodologies for system design and control
  • Statistical, theoretical, and practical issues of input and output analysis
  • Analysis of simulation models for operations research applications such as risk management and queueing systems
  • Simulation of resilient systems and for examining system resilience
  • Interpretation and handling of data variation in simulation models
  • Metamodeling and multimodeling

Aviation Modeling and Analysis

Track Coordinators: Sameer Alam (NTU Singapore), Miguel Mujica Mota (Amsterdam University of Applied Sciences), Michael Schultz (Universität der Bundeswehr München)

The world’s air transportation system is preparing for an influx of new users with diverse needs, while simultaneously growing in its traditional areas. The Aviation Track aims to cover most of the important areas of the aviation industry where simulation alone or together with other techniques can provide solutions. Therefore, we invite researchers from research institutions, universities, airlines, air navigation service providers, and industry to submit original papers presenting results of their work.

Areas of interest are, but not limited to:

  • Human-in-the-Loop simulations for training and for evaluating new technologies
  • Airports
  • Capacity & efficiency improvement
  • Airport capacity forecast
  • Business intelligence for airports
  • Multi-Airport Systems
  • Small and regional airport development
  • Airline operations
  • Maintenance, Repair, and Overhaul and Lean MRO
  • Optimization of operational processes or specific problems in aviation
  • Air Traffic Management
  • ATC/AIRPORT systems
  • Digital / remote tower operations
  • Predictability of air transportation operations
  • Unmanned airborne systems
  • Trajectory modeling
  • Safety of interactions with manned aviation
  • Air traffic control concepts
  • Development of incident investigation
  • Environmental effects of aviation
  • Cargo problems in aviation
  • Multimodality where aviation is involved
  • Economics of the air transportation system
  • Communications, Navigation, and Surveillance systems

Commercial Case Studies

Coordinator: Wendy Jiang (SAS), David Sturrock (Simio LLC)

You might have done important work where you used simulation to conduct analysis and provide recommendations for potential solutions to a specific problem; or where simulation is the backbone of a commercial application enabling critical use cases that you would like to share with others. But perhaps you do not have the time and resources required to submit a full paper and make early commitments to participate at the 2023 Winter Simulation Conference.

To support your commercially focused contributions, you are cordially invited to submit to 2023 WSC a 2-page Extended Abstract describing an industrial or commercial case study. Unlike in previous years, case studies will not be kept in a separate track anymore. Rather, for all application-oriented topics such as the example below, presentations of such case studies will be fully integrated into the respective full paper presentation tracks. This will enable WSC to not only feature more prominently exciting commercial show cases illustrating the benefits that have been achieved with novel methodologies and solutions, but also to much more effectively catalyze cross-fertilization between Academia and Industry.

For more information go to the Commercial Case Studies page.

Complex and Resilient Systems

Track Coordinators: Saurabh Mittal (MITRE Corporation), Claudia Szabo (University of Adelaide)

The increasing integration of the Internet of Things (IoT) technologies emphasize that heterogeneous systems are the norm today. A system deployed in a net-centric environment eventually becomes a part of a larger system of systems (SoS). This SoS also incorporates adaptive and autonomous elements (systems that have different levels of autonomy and situated behavior). This makes design, analysis, and testing for the system-at-hand a complex endeavor itself. Testing in isolation is not the same as a real-system operation, since the system’s behavior is also determined by input, which evolve from the environment. This exact factor is difficult to predict, due to an ever-increasing level of autonomy and environment complexity. Advanced Modeling and Simulation (M&S) frameworks are required to facilitate SoS design, development, testing, and integration. These frameworks must provide methods to deal with intelligent, emergent, adaptive and resilient behavior that encompasses autonomy. The subject of emergent and resilient behavior, and M&S of such behaviors takes the center stage in such systems as it is unknown how a system responds in the face of such behaviors arising out of interactions with other complex systems.

This track is focused on the modeling, simulation, and validation and verification of intelligent, adaptive, complex and resilient systems and how they handle faults, system issues, and emergent behaviors. This track has two objectives.

The first objective aims to focus on M&S of the following aspects of complex SoS engineering with a focus on resilient systems, and brings researchers, developers and industry practitioners working in the areas of complex, adaptive, autonomous and resilient SoS engineering. This objective covers the following topics, but not limited to:

  • Theory for intelligence-based, adaptive, complex and resilient systems
  • Computational intelligence and cognitive systems engineering approaches impacting resilience
  • Human-in-the-loop systems and Human-on-the-loop systems
  • M&S Frameworks for adaptive and resilient behavior
  • Methodologies, tools, and architectures for adaptive control systems
  • Knowledge engineering, generation, and management
  • Weak and Strong emergent behavior, Emergent Engineering
  • Complex adaptive systems engineering
  • Self-* (organization, explanation, configuration) capability and resilient behavior
  • Applications to robotics, unmanned systems, swarm technology, semantic web technology, and multi-agent systems
  • Live, Virtual and Constructive (LVC) environments
  • Modeling, engineering, testing and verification of complex and resilient behaviors
  • Development and testing of complex and distributed systems
  • Modeling, simulating, and testing IoT environments and applications

The second objective is to incorporate Complexity Science in simulation models. Complexity is a multi-level phenomenon that exists at structural, behavioral and knowledge levels in such SoS. Emergent and resilient behavior is an outcome of this complexity. Understanding this complexity will provide a foundation for resilient intelligent systems, and the M&S thereof. Topics related to this objective include, but are not limited to handling of:

  • Complexity in Structure: network, hierarchical, small-world, flat, etc.
  • Complexity in Behavior: Micro and macro behaviors, local and global behaviors, teleologic and epistemological behaviors
  • Complexity in Knowledge: ontology design, ontology-driven modeling, ontology-evaluation, ontology transformation, etc.
  • Complexity in Human-in-the-loop: artificial agents, cognitive agents, multi-agents, man-in-loop, human-computer-interaction
  • Complexity in Human-on-the-loop: trust modeling, human-machine-interaction
  • Complexity in resilience-based systems: Situated behavior, knowledge-based behavior, resource-constrained systems, energy-aware systems
  • Complexity in adaptation and autonomy
  • Complexity in architecture: Flat, full-mesh, hierarchical, adaptive, swarm, transformative
  • Complexity in awareness: Self-* (organization, explanation, configuration)
  • Complexity in interactions: collaboration, negotiation, greedy, rule-based, environment-based, etc.
  • Complexity in LVC environments
  • Complexity in artificial systems, social systems, techno-economic-social systems
  • Complexity in model engineering of complex and resilient SoS
  • Complexity in model specification using modeling languages and architecture frameworks such as UML, PetriNets, SysML, DoDAF, MoDAF, UAF, etc.
  • Complexity in simulation infrastructure engineering: distributed simulation, parallel simulation, cloud simulation, netcentric parallel distributed environments
  • Complexity in Testing and Evaluation (T&E) tools for SoS engineering
  • Complexity in Heterogeneity: Hardware/Software Co-design, Hardware in the Loop, Cyber-Physical Systems, the Internet of Things
  • Metrics for Complexity design and evaluation
  • Complexity in Verification, validation, and accreditation in SoS
  • Complexity of Application in domain model engineering: Financial, Power, Robotics, Swarm, Economic, Policy, etc.
  • Complexity in SoS failure

Data Science for Simulation

Track Coordinators: Abdolreza Abhari (Ryerson University), Hamdi Kavak (George Mason University)

The Data Science for Simulation track aims to promote novel contributions in the use and generation of big data within simulations. This track welcomes all methodological, technical, and application area-focused contributions that advance the modeling and simulation body of knowledge. Some topics of interest include:

  • Big Data in simulation
  • Data analytics for simulation
  • Machine learning methods to generate synthetic data
  • Simulating massive data processing systems
  • Digital Twin Simulations
  • Machine learning and data mining in modeling and simulation
  • Data-Driven techniques for modeling and simulation
  • Deep learning in modeling and simulation
  • Hybrid approaches of combining simulation and machine Learning
  • Simulation initialization techniques using big data
  • Big data management/processing techniques for simulations
  • Ontologies for big data modeling
  • Data science pipelines for modeling for simulations
  • Data science and social networks in simulation
  • Simulation of cloud computing and distributed systems

Environment, Sustainability, and Resilience

Track Coordinators: Elie Azar (Carleton University), Shima Mohebbi (George Mason University)

The Environment, Sustainability, and Resilience track focuses on the theory and application of simulation and modeling to derive innovative and resilient solutions to environmental and sustainability challenges. Application areas include infrastructure systems, cyber-physical systems, ecological systems, renewable resources, transportation, buildings, farming, manufacturing, and urban/city science. We solicit papers presenting new ideas, concepts, models, methods, tools, standards, and applications to achieve sustainability and resiliency in natural and built environments. Possible topics include, but are not limited to:

  • Decision support and analytics for sustainability
  • Smart, connected, and resilient infrastructure
  • Social dynamics and policy innovations of managing sustainable infrastructure systems
  • Simulation and network modeling for resilience assessment
  • Environmental modeling, visualization, and optimization
  • Renewable resources and related processes
  • Smart building systems and robust design
  • Energy/resource-efficient manufacturing
  • Smart and resilient grids
  • Information modeling and interoperability
  • Energy-efficient and sustainable urban planning and design
  • Smart transportation systems
  • Human-environment interaction
  • Ecological systems
  • Natural disasters and their impact on society and engineered systems
  • Environmental risk assessment and mitigation
  • Human adaptation to climate

Healthcare and Life Sciences

Track Coordinators: Bjorn Berg (University of Minnesota), Masoud Fakhimi (University of Surrey), Tugce Martagan (Eindhoven University of Technology)

The Healthcare and Life Sciences track addresses important areas in which simulation can provide critical decision support for operational and strategic planning and decision making that individual providers (doctors/nurses, clinics, urgent care centers, hospitals) face, as well as for policy issues that must be addressed by administering systems (e.g., hospitals, insurance companies, and governments). Traditionally, this track has been broad in focus, incorporating Discrete Event Simulation, System Dynamics, Agent-Based Simulation, and/or Monte Carlo simulations, with a variety of applications. A common thread is the use of simulation tools to provide insight into, or to inform, decisions for improved healthcare performance measures and outcomes. New modeling tools that address challenges with the conceptualization or implementation of healthcare systems, and general healthcare simulations are welcome. Topics include, but are not limited to, the following:

  • Admissions and control
  • Ancillary services
  • Appointment scheduling
  • Emergency room access
  • Epidemic and pandemic modeling
  • General healthcare simulation
  • Global Health
  • Healthcare optimization
  • Healthcare systems
  • Medical decision making
  • Outpatient access
  • Outpatient capacity analysis
  • Payment/Payer models
  • Performance improvement models
  • Pricing models
  • Resource scheduling (e.g., nurse, doctor, anesthesiologist, residents, equipment, etc.)

Hybrid Simulation

Track Coordinators: Anastasia Agnostou (Brunel University), Antuela Tako (Loughborough University)

The Hybrid Simulation track welcomes submissions presenting work on the combination of various simulation and analytics methods. Unlike the conventional M&S approaches, where techniques are applied in isolation, the submissions we wish to attract will describe research and practice in the combined application of multiple methods, thereby providing greater synergy in the solution model and deeper insights to the problem. More specifically, we are looking for work that showcases the combination of different simulation techniques (e.g., Discrete-Event Simulation, Monte Carlo simulation, System Dynamics, Agent-Based Simulation) and/or the combination of M&S with analytics techniques from other disciplines such as Continuous Simulation, Computer Science/Applied Computing, Problem Structuring Methods, Artificial Intelligence, Business Analytics, Data Science, Systems Engineering, Economics, Humanities and Psychology, etc.

Topics include, but are not limited to, the following:

  • Synthesis of existing literature reviews and comparison studies in HS and HSM providing taxonomies of the hybrid modelling and simulation field.
  • Methodology focusing on the development of frameworks and modelling formalisms to support hybrid modelling and simulation.
  • Studies presenting case study applications of hybrid simulation and modelling in various domains
  • Technical papers on the development of software artefacts for supporting hybrid simulation and modelling.
  • Conceptual modelling for hybrid simulation and modelling
  • Papers on validation and verification of hybrid simulation and modelling
  • The combined application of modelling approaches, e.g. ABS-SD- DES
  • The combined use of Simulation with methods and techniques from other disciplines, e.g., ABS and metaheuristics, predictive analytics and simulation, DES and game theory, DES and SSM, etc.
  • Application of hybrid simulation in behavioral studies (commonly referred to as Behavioral Operations Research)

Introductory Tutorials

Track Coordinators: Sanjay Jain (George Washington University), Chang-Han Rhee (Northwestern University)

The Introductory Tutorials track is oriented toward professionals in modeling and simulation interested in broadening or refreshing their knowledge of the field. Tutorials cover all areas including mathematical and statistical foundations, methods, application areas, software tools and analysis tools.  

Logistics, Supply Chain Management, Transportation

Track Coordinators: David Goldsman (Georgia Institute of Technology), Zhao Lei (Tsinghua University), Markus Rabe (Technische Universität Dortmund)

The nature of today’s highly dynamic, stochastic, and complex networks of supply, intralogistics, and distribution has led to decreasing transparency of the enterprises’ processes, while at the same time increasing failure risks. This also applies for deliveries to the end customer, e.g., at collection points or at home delivery. In addition, pollution and climate change have created a demand for new concepts in urban logistics as well as careful planning in this uncertain field. Therefore, managers who are responsible for supply chain management and logistics require effective tools to provide credible analysis in this challenging environment. In order to facilitate the discussion of the best applications of simulation in this timely area, the LSCT track includes papers in logistics simulation, supply chain simulation, and simulation for planning, analyzing, and improving transportation in a wide scope encompassing topics from the detailed intralogistics level up to global supply chains. Topics of interest include, but are not limited to, the following:

  • Green supply chain design
  • Supply chain resilience
  • Big data analytics for supply chains
  • Supply chain risk analysis
  • Simulation-based optimization of supply chains
  • Supply chain operations
  • Demand and order fulfillment
  • Inventory policies
  • Intralogistics and advanced material flow systems
  • Online purchase delivery concepts
  • Omni-channel logistics
  • Crowdshipping
  • Urban transport
  • Last-mile logistics
  • Multi-modal logistics systems
  • Port operations
  • Rail operations
  • Road networks

Manufacturing & Industry 4.0

Track Coordinators: Alp Akcay (Eindhoven University of Technology), Christoph Laroque (University of Applied Sciences Zwickau), Gordon Shao (NIST)

Simulation is the model-based methodology for analyzing dynamical inter-dependencies in manufacturing systems. The Manufacturing Applications track is interested in research work using simulation in industrial applications as found in the automotive, aircraft and shipbuilding industries, among others. Manufacturing applications relate to the model-based analysis of (i) all production and logistics processes within a company or along a supply chain, and (ii) all phases of a system life cycle, such as system acquisition, system design and planning, implementation, start of operation and ramp-up, as well as the operations itself. A contribution shall describe the aims of investigation, the investigated system, the simulation model, the experimental plan, the findings, and any implementation results. Additionally, specific challenges like system complexity, data collection and preparation, or verification and validation may be pointed out. Topics include, but are not limited to, the following:

  • Manufacturing
  • Applications of simulation-based optimization in production
  • Cyber-physical systems, Industry 4.0 / Industry 5.0
  • Production planning and scheduling
  • Lean management
  • Total Quality Management
  • Maintenance and Lifecycle-Assessment
  • Integration of energy and carbon footprint
  • Digital Production Twins

Military and National Security Applications

Track Coordinators: Clay Koschnick (Air Force Institute of Technology), James Starling (U.S. Military Academy)

The Military and National Security Applications Track is interested in papers that describe the application of modeling and simulation theory, techniques, tools and technologies to challenges in the military and national security domain. Example application areas include: battle management command and control, air and missile defense, campaign analysis, weapon-target pairing, multi-domain operations, sustainment operations, operational testing and evaluation, wargaming and assessments, CBRNE defense, critical infrastructure analysis, homeland defense and domestic civil support operations, cybersecurity, information operations, electronic warfare, intelligence, surveillance and reconnaissance, medical and healthcare operations, manpower and personnel, readiness and training, cost, risk and decision analysis, special operations, etc.

Topics of special interest include, but are not limited to, challenges and innovations for representation and implementation of command, control and communications, swarm intelligence, cybersecurity operations, cyber threat intelligence, social media analytics, hardware-in-the-loop simulations, human-machine teaming, future platforms and weapons prototyping, synthetic environments, multi-sensor fusion, complex behaviors of semi-automated forces, electronic warfare, expeditionary medical operations, automatic scenario planning and experimentation, and multi-resolution models. Papers investigating an innovative use of edge/fog/cloud technologies, gaming technology, mixed reality technology, artificial intelligence and machine learning technology, big data technologies, distributed computing technology, and networking technology for military and national security applications are also welcome!

Modeling & Analysis of Semiconductor Manufacturing (MASM)

Track Coordinators: John W. Fowler (Arizona State University), Lars Mönch (University of Hagen),
Young Jae Jang (KAIST) 

Click here for more information.

Modeling Methodology

Track Coordinators: Rodrigo Castro (University of Buenos Aires), Andrea D’Ambrogio (University of Rome Tor Vergata), Gerd Wagner (Brandenburg University of Technology), Gabriel Wainer (Carleton University)

The Modeling Methodology track is interested in methodological advances with respect to the theory and practice of modeling and simulation. These may include approaches to model development, model building, verification, validation, experimentation, and optimization. Contributions to the advancement of the technology and the software used to support modeling are also welcome as are contributions featuring guiding or unifying frameworks, the development and application of meaningful formal methods, and lessons learned.

This year, there will be a panel and 1-2 special sessions on “Forty Years of Event Graphs”, for which papers may be submitted. If you have an idea for a special session or a panel discussion of particular interest to the WSC participants, please send an email with a short description and references to the work of relevant experts to the track chairs. Topics of interest include, but are not limited to, the following:

  • Modeling paradigms
  • Formal modeling languages
  • Modeling approaches for real-time systems and Cyber-Physical Systems
  • Multi-paradigm/formalism modeling
  • Model reuse, repositories, and retrieval
  • Modeling with ontologies
  • Model standardization
  • Model operations and model lifecycle governance
  • Modeling approaches for complex socioeconomic systems and emergent behavior

PhD Colloquium

Chair: Siyang Gao (City University of Hong Kong)
Members: Anatoli Djanatliev (Friedrich-Alexander-Universität Erlangen-Nürnberg), Cristina Ruiz Martin (Carleton University), Eunhye Song (Georgia Institute of Technology)

In 2023, ACM-SIGSIM and INFORMS-Sim will once again sponsor the Ph.D. Colloquium for Ph.D. students that are within two years of graduation (planning to graduate by December 2025). Students close to graduation will be given an opportunity to showcase their work during a short presentation session during the Colloquium (apart from the regular tracks). Presenting your Ph.D. work to your peers and the larger simulation community will give you the opportunity to receive valuable feedback and ideas, as well as introduce you to a network that can be very helpful for your career once you graduate.

Go to the PhD Colloquium page for additional details. 

Poster Session

Track Coordinator: Maria Blas (INGAR CONICET-UTN), Zeyu Zheng (University of California, Berkeley)

The Poster Session offers a timely venue to present and discuss new modeling and simulation research through a forum encouraging graphical presentation, demonstration, and active engagement among Winter Simulation Conference (WSC) participants.

We are seeking outstanding extended abstracts (2 pages) submissions to be presented in a poster format at the conference. Competitive contributions will present interesting recent results, novel ideas or works-in-progress that are not quite ready for a regular full-length paper. Contributions from Ph.D. students are particularly welcome. Submitted manuscripts should follow the standard template for WSC submission, and should not exceed the 2 pages limit. Extended abstract submissions are encouraged in all areas of modeling and simulation covered by WSC. 

Please refer to the Poster Session page for more information.

Professional Development

Track Coordinators: Tom Berg (University of Tennessee-Knoxville), Weiwei Chen (Rutgers University)

This track focuses on enhancing the professional practice of simulation modeling and analysis by providing the means for those in the profession to improve communication, leadership, planning, problem-solving, research, project management, teaching skills, and examples of model applications in industry, as they relate to simulation activities. We encourage sessions focused on graduate students who are looking for jobs in industry, challenges faced by women and underrepresented minorities, early-career academics, etc. Also, since a key aspect of professional development oftentimes involves credentialing, this track explores the need for, and means to, certify simulation modelers and analysts.

Project Management and Construction

Track Coordinators: Eric Du (University of Florida), Joseph Louis (Oregon State University)

The Project Management and Construction track includes innovative research as well as practical application papers that apply computer simulation to complex project and construction management problems. Computer simulation encompasses a broad range of data-driven, quantitative methods including, but not limited to:

  • Discrete event simulation
  • Continuous simulation
  • System dynamics
  • Big data analytics
  • Virtual/Augmented reality
  • Automation and robotics
  • Emerging AI techniques

    Applications include, but are not limited to
  • Complex project planning and scheduling
  • Planning for integrated project delivery
  • Construction safety planning
  • Off-site production and modularization systems
  • Site operations and layout planning
  • Human behavior and organization modeling
  • Sustainable built environment
  • Simulation as a project management education tool
  • Lean production systems
  • Sensed environments for simulation
  • Project portfolio management
  • System optimization and control

Reliability Modeling and Simulation

Track Coordinators: : Sanja Lazarova-Molnar (University of Southern Denmark), Olufemi Omitaomu (Oakridge National Lab), Li Xueping  (University of Tennessee-Knoxville)

Complex real-time systems need to have their dependability and reliability evaluated and addressed to ensure that systems perform satisfactorily despite the presence of faults. Systems’ design decisions are also influenced by these evaluations. Simulation has often been utilized for this purpose. This track covers the use of modeling and simulation for analysis of reliability and dependability of systems. Further relevant topics are listed as follows:

  • data-driven reliability modeling
  • simulation for optimizing repair and maintenance strategies
  • reliability models for hardware and software
  • reliability modeling of cyber-physical systems
  • modeling and simulation of fault-tolerant systems
  • fault models and fault abstraction
  • reliability modeling formalisms
  • dependability analysis using simulation and experimental measurement
  • case studies of using simulation for reliability analysis

Scientific Artificial Intelligence (AI) &  Applications

Track Coordinators: Rafael Mayo-García (CIEMAT), Esteban Mocskos (Universidad de Buenos Aires)

The ‘Scientific AI and Applications’ track is focused on theory, experimentation, and engineering practices that form the basis for the design and use of simulation methodologies in science, including artificial intelligence and evolutionary algorithms. The objective of the track is to be a point of transversal communication in which methodologies, techniques, tools, and practical issues in any specific scientific domain can be extended and adopted by others.

According to the general WSC 2023 motto, contributions addressing resilience are very welcome. Hence, topics of interest include, but are not limited to:

  • Application of Artificial Intelligence for solving simulated phenomena
  • Applied simulation methodologies
  • Challenges in performance evaluation of scientific applications
  • Data-driven workflows
  • Evolutionary algorithms applied in science
  • Large-scale debugging and analysis tools
  • Modeling tools and frameworks
  • Networking technologies in scientific applications
  • Scaling methodologies
  • Scientific data retrieval, storage, and processing
  • Successful use cases
  • Support for the development of scientific applications
  • Usage of new technologies and architectures

Simulation and Artificial Intelligence

Track Coordinators: Edward Hua (MITRE Corporation), Yijie Peng (Peking University), Simon Taylor (Brunel University)

Simulation is important area of Operations Research, and it has many advantages in analyzing the performance of complex stochastic models. AI also has many advantages, especially when there are rich sources of data. The combination of the methodologies of the two areas presents many exciting opportunities.  For example, simulation plays a central role in deep learning and reinforcement learning, which are the foundation of AI, and it can continue improving the AI techniques, particularly in addressing some of its bottlenecks. AI techniques have also contributed to recent advances of simulation research. This track invites papers and presentations about state-of-the-art research at the intersection of simulation and AI. Potential topics include, but are not limited to:

  • Simulation and AI methodologies
  • Simulation-based machine learning
  • AI-boosted Simulation modeling and optimization
  • Applications of Simulation and AI

Simulation Around the World

Track Coordinator: Seong-Hee Kim (Georgia Institute of Technology), Theresa Roeder (San Francisco State University)

WSC 2023 establishes a new track “Simulation Around the World” (SATW) whose primary goal is to broaden outreach to researchers in:

  • Geographical regions that are historically underrepresented in WSC (e.g., South America and Africa); or
  • Countries where travel is prohibited or challenging due to exceptional national circumstances such as war or disaster, but excluding COVID-related restrictions.

If accepted to the SATW track, registration will be free. In addition, accepted applicants will be able to remotely present their research in one of the SATW sessions and attend other sessions in the same track virtually. Presentations will be given in a synchronous hybrid fashion, with live audience participation from in-person attendees of the conference.

Full papers or extended abstracts must be submitted online at

When submitting a paper or extended abstract to this track, please select one of the following options when filling out the submission form:

  • Simulation Around the World Contributed Paper, or
  • Simulation Around the World Contributed Extended Abstract.

The submission requirements and deadlines are the same as for regular contributed papers or extended abstracts. Additionally, authors will need to provide a short statement of no more than 250 words explaining how their submission aligns with the goals of the SATW track. The track committee will review all applications to determine the suitability for the SATW track. Applications will also be reviewed for technical merit following the standard review process.

Simulation as Digital Twin

Track Coordinators: Andrea Matta (Politecnico di Milano), Jie Xu (George Mason University)

Simulation is a relevant enabling technology for fully exploiting data streams to make fast predictions, quantifying continuous improvement actions and making smart decisions in real-time. The Digital Twin track is interested in research contributions on simulation theory and applications to support, embedded in closed-loop controls, complex processes such as production, logistics, service delivery, etc. A particular interest is on models and algorithms to create, update, and keep synchronised simulation models with physical systems. Data-driven approaches are also well aligned with the track being the enablers for skill-free technologies. Contributions describing physical and digital laboratories to test new models, methods, and tools for simulation as digital twin are also appreciated. Topics include, but are not limited to, the following:

  • Data-driven simulation modeling & validation
  • Production planning and control
  • Real time simulation-based control
  • Simulation-based optimization
  • On-line validation
  • Synchronisation physical-to-digital
  • Cyber-physical systems
  • Digital Twins
  • Manufacturing
  • Transportation and logistics
  • Automated warehouses
  • Operations and supply chains
  • Maintenance
  • Healthcare systems
  • Traffic control
  • Service systems

Simulation in Education

Track Coordinators: Omar Ashour (Penn State University), Christopher Lynch (Old Dominion University)

The Simulation in Education track aims to share pedagogical, andragogical, and didactic approaches that employ or promote the use of simulation in education. These approaches could utilize technology-enhanced environments (e.g., video games, simulations, mixed reality, pervasive computing), non-technology environments/approaches (e.g., Lego simulations and role-play), or a combination of both. The track is focused on educators and trainers who are interested in incorporating simulations into classrooms, and/or training programs to educate the next generation of scientists, engineers, healthcare professionals, artists, humanists, and social scientists. It is for anyone interested in learning and developing the skills necessary to teach simulation. All learning delivery modes and situations are of interest, i.e., in-person vs remote learning, formal vs informal learning, K-12, higher education, professional training, continuing education, adult learning, etc.  

The track seeks work from all disciplines including but not limited to engineering, science, medicine, arts, humanities, and social sciences. The sessions in this track will cover a wide range of topics including but not limited to:

  • The design and development of simulation methods
  • Teaching, learning, and assessment approaches for simulation education
  • Use of technology and immersive environments in education (virtual reality, augmented reality, mixed reality, video games, artificial intelligence, etc.)
  • Best practices and case studies of using simulation in education
  • New tools and techniques for using simulation in education
  • Challenges in implementing simulation in education
  • Hands-on workshops or demonstrations of simulation software packages
  • Simulation-based and experiential learning

Simulation Optimization

Track Coordinators: David Eckman (Texas A&M University), Siyang Gao (City University of Hong Kong)

The Simulation Optimization track focuses on the design, analysis, and application of algorithms that can be coupled with computer simulations to identify decision variable values that optimize one or more simulation performance measures of interest.  This track is interested in papers on the development of new algorithms accompanied by analysis of the algorithm’s theoretical, empirical, and computational performance. The track also welcomes papers that compare existing simulation-optimization algorithms or apply them on real-world problems. Topics of interest include, but are not limited to,

  • Global and black-box optimization
  • Simheuristics
  • Metaheuristics
  • Discrete optimization via simulation
  • Ranking & selection
  • Stochastic programming
  • Sample average approximation
  • Stochastic approximation methods
  • Metamodel-based methods
  • Multi-objective optimization
  • Optimization with stochastic constraints
  • Approximate dynamic programming and reinforcement learning
  • Optimal learning
  • Active learning
  • Multi-armed bandit methods

Uncertainty Quantification & Robust Simulation

Track Coordinators: Xi Chen (Virginia Tech), Wei Xie (Northeastern University)

The Uncertainty Quantification and Robust Simulation track aims to cover mathematical, statistical, algorithmic, and application advances in uncertainty quantification and robust simulation, which facilitate characterization, quantification, and management of various sources of uncertainty inherent in the use of simulation models. The sources of uncertainty include the observation errors in real-world data sets used to calibrate the input models and validate the simulation model, structural uncertainty, numerical uncertainty, etc. These uncertainties can impact, e.g., simulation-based predictive accuracy, simulation optimization, sensitivity analysis, prediction, and feasibility assessment in various ways and to different extents. Papers investigating various sources of uncertainty and their impacts that are broadly defined are welcome. Contributions can include the development of quantification criteria, novel statistical or mathematical methods to assess the impacts of different sources of uncertainty or errors, the efficiency analyses or improvements of existing methods, and applications of these methods in different domain contexts. Topics of interest include, but are not limited to:

  • Input uncertainty quantification criteria and methods
  • Robustness in input modeling and selection
  • Model risk quantification and reduction
  • Model calibration and validation
  • Data assimilation
  • Risk-sensitive simulation optimization
  • Robustness against simulation logic or model misspecifications
  • Sensitivity analysis


Track Coordinators: Manos Thanos-Filis (GE Research), Edward Williams (University of Michigan and PMC)

In addition to the Sunday Workshops, exhibitors have the opportunity to participate in the Vendor Track at WSC. The Vendor Track provides an opportunity for companies that market modeling and simulation technology and services, or related services (e.g., statistical analyses) to present their innovations and successful applications.

For each slot in the Vendor Track, there are two available options: submit a complete paper or an abstract. Abstracts and papers appear online and in the final program, but neither appear in the archival proceedings (due to IEEE rules). Abstracts are lightly reviewed by the track coordinator and papers are reviewed by multiple members of committee and may entail revisions. Papers and abstracts must use the Authors Kit in order to adhere to the publication format requirements. The submission deadline for abstracts is October 6, 2023.  More details on Paper Submission/Formats