Advanced Tutorials

Track Coordinators: Wai Kin “Victor” Chan Wai Kin (Tsinghua-Berkeley Shenzhen Institute), Wan Hong (North Carolina 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: Stephan Onggo (University of Southampton), Chris J. Kuhlman (University of Virginia)

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 platform 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
  • Applications
  • 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: Wei Xie (Northeastern University), Luo Jun (Shanghai Jiaotong University), David Eckman (Texas A&M 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
  • Simulation for risk management
  • Interpretation and handling of data variation in simulation models
  • Metamodeling and multimodeling
  • Epistemological issues of simulation analysis

Aviation Modeling and Analysis

Track Coordinators: John Shortle (George Mason University), Miguel Mujica Mota (Amsterdam University of Applied Sciences)

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
  • 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 & Industrial Case Studies

To support your commercially focused contributions, you are cordially invited to submit to WSC 2022 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 (see below for the full list), 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 & Industrial Case Studies page.

Application Oriented Tracks:

  • 18th International Conference on Modelling and Analysis of Semiconductor Manufacturing (MASM)
  • Aviation M&A
  • COVID-19 and Epidemiological Simulations
  • Complex and Resilient Systems
  • Data Science and Simulation
  • Environmental and Sustainability Applications
  • Financial Engineering
  • Gaming and Participatory Methods
  • Healthcare Applications
  • Logistics, Supply Chains, Transportation
  • Manufacturing Applications
  • Maritime Systems
  • Military and National Security Applications
  • Project Management and Construction
  • Reliability Modeling and Simulation
  • Scientific Applications
  • Simulation as Digital Twin
  • Simulation and AI

Complex and Resilient Systems

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

This track is focused on the modeling, simulation, and validation of intelligent, adaptive, and complex systems and how they handle faults, system issues,  and emergent behaviors. The increasing popularity of the Internet of Things (IoT) metaphor emphasizes that heterogeneous systems are the norm today. A system deployed in a net centric environment eventually becomes a part of a system of systems (SoS). This SoS also incorporates adaptive and autonomous elements (such as 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 the input, which evolves from the environment. This exact factor is difficult to predict, due to an ever-increasing level of autonomy and complexity. Advanced Modeling and Simulation (M&S) frameworks are required to facilitate SoS design, development, testing, and integration. In more particular, these frameworks must provide methods to deal with intelligent, emergent, and adaptive behavior as well as autonomy.

The subject of emergent behavior and M&S of emergent behaviors takes the center stage in such systems as it is unknown how a system responds in the face of emergent behavior arising out of interactions with other complex systems. Intelligent behavior is also defined as an emergent property in some complex systems. Consequently, systems that respond and adapt to such behaviors may be called intelligent systems as well.  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 and autonomous SoS engineering. This objective covers the following topics:

  • Theory for intelligence-based, adaptive and complex systems
  • Computational intelligence and cognitive systems
  • Human-in-the-loop systems and Human-on-the-loop systems
  • M&S Frameworks for intelligent 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 collaborative behavior
  • Applications to robotics, unmanned vehicles systems, swarm technology, semantic web technology, and multi-agent systems
  • Live, Virtual and Constructive (LVC) environments
  • Modeling, engineering, testing and verification of complex behavior
  • 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 behavior is an outcome of this complexity. Understanding emergent behavior as an outcome of 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 intelligence-based systems: Situated behavior, knowledge-based behavior, mnemonic 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 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 n SoS
  • Complexity of Application in domain model engineering: Financial, Power, Robotics, Swarm, Economic, Policy, etc.
  • Complexity in SoS failure

Covid-19 and Epidemiological Simulations

Track Coordinator:  Edward Huang (Geroge Mason University), Xiao Hui  (Southwestern University of Finance and Economics)

This track is focused on both the use of modeling and simulation to solve problems associated with the COVID-19 pandemic or any other type of epidemiological models. The COVID-19 pandemic has offered a wide variety of opportunities to apply simulation to immediate problems affecting hundreds of lives and has brought epidemiological modeling world wide attention. Application areas are broad and can include public health, hospitals, schools and universities, restaurants, infrastructure, transportation, logistics, and so on. We solicit papers presenting new ideas, models, methods, and tools related to epidemiology or solving problems that have arisen due to the pandemic.

DSS – Data Science and Simulation

Track Coordinators: Abdolreza Abhari (Ryerson University), Chen Cheng-bang  (University of Miami), Mani Sharifi (Ryerson 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 topic of interests includes:

  • 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 and Sustainability Applications

Track Coordinators: Elie Azar (Khalifa University)

The Environment and Sustainability Applications track focuses on the use of modeling and simulation to drive innovative and smart solutions to environmental and sustainability challenges. Application areas include infrastructure, ecological systems, renewable resources, buildings, transportation, manufacturing, and urban planning. We solicit papers presenting new ideas, concepts, models, methods, tools, standards, and applications to achieve sustainability and resiliency in natural and man-made environments.

Possible topics include, but are not limited to:

  • Decision support and analytics for sustainability
  • Smart, robust, and resilient infrastructure
  • Environmental modeling, visualization, and optimization
  • Renewable resources and related processes
  • Smart building systems and robust design
  • Energy/resource-efficient manufacturing
  • Smart 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
  • Environmental risk assessment and mitigation
  • Human adaptation to climate

Financial Engineering

Track Coordinators: Ben Feng  (University of Waterloo), Liu Guangwu  (City University of Hong Kong)

The Financial Engineering Tract aims to include methodological and practical research in finance, financial markets, risk measures, risk management, FinTech (financial technology) and InsurTech (insurance technology). Simulation designs, input/output analysis, and sensitivity analysis in all aspects of financial risk management are welcome. Specifically, papers that introduce new simulation methodologies and applying standard methodologies in new financial applications are both encouraged. Emerging topics in risk management are highly encouraged. Suggested sessions include, but not limited to, the following:

  • FinTech and financial markets
  • Risk measures, Basel IV, and IFRS 17
  • Nested simulation for risk management
  • Risk management and modeling for climate change and carbon credits
  •  Insurance risk management for pension, mortality and longevity, aging, and post-retirement
  • Economic scenario generators (ESGs) with machine learning and predictive analytical models
  • Risk management with Internet of Things (IoTs): wearable devices, self-driving cars, and security cameras.

Gaming and Participatory Methods

Track Coordinators: Sebastiaan Meijer (KTH Royal Institute of Technology), Jayanth Raghothama (KTH Royal Institute of Technology)

The Gaming track deals with the intersection of games and other participatory methods and simulation in application domains such as business, management, entertainment, training, military, and medical sciences. The natural tension between rigor in modeling and the free and playful interaction with a simulated system through gaming will be addressed. Gaming in combination with simulation has applications in entertainment, learning, training, policymaking, decision support, and design. The track also focuses on the use of gaming techniques and technologies to enhance the usability of simulations, for example with innovative visualization and interactive techniques, as well as on the use of simulation techniques in game design and development.

Healthcare Applications

Track Coordinators: Christine Currie (University of Southampton), Masoud Fakhimi (University of Surrey), Berg Bjorn (University of Minnesota)

The Healthcare Applications track addresses an important area 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 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 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: Antuela Tako (Loughborough University), Caroline Krejci (The University of Texas at Arlington), Andrew J. Collins (Old Dominion University)

The  Hybrid Simulation track welcomes submission on Hybrid Simulation (HS) or Hybrid Systems Modelling (HSM) from authors that have used a combination of various simulation and analytics, with the objective of overcoming the limitations associated with using individual methods. Unlike the conventional M&S approaches, where techniques have been 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, HS is a combination of different simulation techniques, e.g., Discrete-Event Simulation, Monte Carlo simulation, System Dynamics, Agent-Based Simulation. HSM is a combination of M&S with analytics techniques from disciplines such as Continuous Simulation, Computer Science/Applied Computing, Business Analytics, Data Science, Systems Engineering, Economics, Humanities and Psychology.

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: Anastasia Anagnostou (Brunel University), Canan Gunes Corlu (Boston 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), Markus Rabe (Technische Universität Dortmund), Zhao Lei (Tsinghua University)

The nature of today’s highly dynamic and complex networks of supply, intralogistics, and distribution has led to decreasing transparency of the processes, while at the same time increasing failure risks. 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:

  • Supply chain design
  • Supply chain responsiveness
  • Supply chain risk analysis
  • Statistical analysis of supply chains
  • Simulation-based optimization of supply chains
  • Green supply chains
  • Supply chain operations
  • Demand and order fulfillment
  • Inventory policies
  • Multi-modal logistics systems
  • Port operations
  • Rail operations
  • Efficient transportation in supply chains
  • Intralogistics
  • Advanced material flow systems
  • Big data analytics for supply chains

Manufacturing Applications

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

Simulation is a well-established model-based methodology for analyzing dynamical inter-dependencies in manufacturing systems. The Manufacturing Applications track is interested in research 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 operation itself. A contribution shall describe the aims of investigation, the investigated system, the simulation model, the experimental plan, the simulation 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, Industrial Internet and Industry 4.0
  • Production planning and scheduling
  • Lean management
  • Total quality management
  • Maintenance and Lifecycle-Assessment
  • Integration of energy and carbon footprint
  • Digital Twin

Maritime Applications

Track Coordinators: Cao Xinhu  (National University of Singapore), Fu Xiuju (Institute of High Performance Computing ), Sun Zhuo (Dalian Maritime University)

The maritime logistics industry plays a critical role in the global supply chain network since ports and ships handle over 80% of trade in volume. Currently, this traditional industry is upgrading from labor-intensive to automated/autonomous operation due to the higher requirement for efficiency and the shortage of skilled human resources. Thus, it calls for rising demands for computer-aided decision-making. Apart from the above challenges, the more frequent Black Swan events have also brought the need to study the non-existed scenarios to the frontstage. As an effective tool for computer-aided decision-making, simulation shows its merits in modeling real-life and non-existed systems. Therefore, the maritime logistics industry has widely adopted it to evaluate decisions in both planning and operation phases. In order to facilitate the discussion of the best applications of simulation in this industry, the Maritime Logistics track includes papers in port simulation, ship route simulation, inland logistics network simulation, disruption simulation, etc. Topics of interest include, but are not limited to, the following:

  • Port layout design
  • Port equipment configuration
  • Port operation rules design
  • Port risk analysis and disruption management
  • Statistical analysis of port systems
  • Simulation-based optimization of ports
  • Green and sustainable ports
  • Intermodal logistics via ports
  • Inland logistics network design
  • Inland logistics operations
  • Shipping route design
  • Shipping fleet deployment and management
  • Efficient maritime transportation
  • Big data analytics for the maritime logistics industry


Track Coordinators: John Fowler (Arizona State University), Lars Mönch (Fernuniversität Hagen), Kan Wu (Chang Gung University)

Click here for more information.

Military and National Security Applications 

Track Coordinators: Nate Bastian (United States Military Academy), 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 Uncertainty and Robust Simulation

Track Coordinators:  Zhou Enlu (Georgia Institute of Technology), Hu Zhaolin  (Tongji University)

The Model Uncertainty and Robust Simulation track aims to cover methodologies and theories that analyze, quantify, reduce or handle errors in simulation analysis due to the uncertainties and risks in the model-building process. These uncertainties include, for example, the statistical noises from real-world data sets used to calibrate input models and to validate the final simulation model, unobserved aspects of the system logic, and non-stationarities. These uncertainties can impact, in various ways and degrees, the accuracy in simulation-based performance prediction, simulation optimization, sensitivity analysis and, feasibility assessment. Papers investigating these uncertainties and their impacts broadly defined are welcome. Contributions can include the development of quantification criteria or methods to assess the impacts of these uncertainties or errors, the efficiency analyses or improvements of these methods, and illustrations of these methods in application contexts. They can include statistical techniques to jointly handle model errors and Monte Carlo or other computational noises, and to assimilate data or validate different aspects of the simulation model. They can also include assessment of robustness against model mis-specifications, based either on data or subject domain knowledge. Topics of interest include, but are not limited to, the following:

    • Input uncertainty quantification criteria and methods
    • Robustness in input modeling and selection
    • Model risk quantification
    • Uncertainty in model calibration and validation
    • Risk-sensitive simulation optimization
    • Robustness against simulation logic mis-specifications
    • Sensitivity analysis on input parameters or distributions

Modeling Methodology

Track Coordinators: Rodrigo Castro (Universidad de Buenos Aires), 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. 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
  • Technological advances in modeling software
  • Spatial and temporal modeling
  • Multilevel modeling
  • Multi-paradigm modeling
  • Multi-formalism modeling
  • Model reuse, repositories, and retrieval
  • Parallel and Distributed simulation
  • Modeling with ontologies
  • Semantic tools supporting modeling methods
  • Standardization challenges
  • Modeling and Simulation for Cyber-Physical Systems

Poster Session

Track Coordinator: Maria Blas (INGAR CONICET-UTN), Xu Jie (George Mason University)

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: Kim Seong-Hee (Georgia Institute of Technology), Chen Weiwei  (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, and teaching skills 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.

No full-length paper is necessary — only a 150-word abstract and a two-page extended abstract is required to be submitted for consideration. The extended abstract should describe the proposed special sessions, workshops, tutorials, and panel sessions. Contributions selected for presentation at WSC will have their abstract appear in the final program of WSC and on the WSC Archive website. Professional Development track papers should use the standard template for submission; please adhere to the two-page length limit. These activities will not count towards WSC’s rule of one paper per single registration.

The submission deadlines are also much more relaxed than for full papers – submissions are in August with final editing in September (see the official Call for Papers for details). If you have an idea for this track, please email a description of proposed session to the track co-chairs.

Project Management and Construction

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

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), Li Xueping  (University of Tennessee-Knoxville), Olufemi Omitaomu (Oakridge National Lab)

Complex real-time systems design needs to address dependability and reliability requirements to ensure that systems perform satisfactorily despite the presence of faults. This track covers the use of simulation for analysis of reliability and dependability of systems, focusing on fault modeling and simulation and associated challenges. 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 Applications

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

The Scientific Applications track is focused on theory, experimentation, and engineering practices that form the basis for the design and use of simulation methodologies in science. 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. Topics of interest include, but are not limited to:

  • Modeling tools and frameworks
  • Applied simulation methodologies
  • Successful use cases
  • Scaling methodologies
  • Support for the development of scientific applications
  • Large-scale debugging and analysis tools
  • Usage of new technologies and architectures
  • Networking technologies in scientific applications
  • Scientific data retrieval, storage, and processing
  • Challenges in performance evaluation of scientific applications

Simulation and AI

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

Simulation has been an important area of Operations Research, and it has many advantages in analyzing the performance of complex stochastic models. Recently, AI has been gaining steam and fundamentally reshaped many areas. 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. The AI techniques have also contributed to recent advances of the 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
  • Simulation and AI in parallel computing environment
  • Applications of simulation and AI

Simulation as Digital Twin

Track Coordinators: Andrea Matta (Politecnico di Milano), Geng Na (Shanghai Jiaotong University), Wang Yuan  (Singapore University of Social Science)

The industry 4.0 wind has reinforced the interest of the society on manufacturing and its intrinsic need of being efficient and effective, the survival of industrial companies from competition largely depends on this. Among Industry 4.0 pillars, 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 Simulation as 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 scheduling
  • Real time simulation-based control
  • Simulation-based optimization
  • Cyber-physical systems
  • Digital Twins
  • Manufacturing
  • Transportation and logistics
  • Operations and supply chains
  • Maintenance
  • Healthcare systems
  • Service systems

Simulation Down Under

Track Coordinators: David Post (CSIRO) and John Fowler (Arizona State University)

Australia and New Zealand boast a very strong field of researchers working in numerical modelling and simulation. Many of these researchers are members of the Modelling and Simulation Society of Australia and New Zealand (MSSANZ) which runs the biennial ‘MODSIM’ conference. This joint MSSANZ/WSC track invites researchers working in Australia and New Zealand to submit a 2-page extended abstract for either in-person or virtual presentation.

While all aspects of modelling and simulation are welcomed, those dealing with techniques to improve the management of Australia and New Zealand’s natural resources are particularly encouraged.

Simulation Optimization

Track Coordinators: Gao Siyang  (City University of Hong Kong), Jiang Guangxin  (Harbin Institute of Technology), Giulia Pedrielli (Arizona State University)

The Simulation Optimization track focuses on algorithms that can be coupled with computer simulations to locate specific decision variable values for the simulation that maximize or minimize a simulation performance measure of interest.  This track is interested in papers on both theoretical aspects of algorithm development and applied aspects of simulation optimization pertaining to computational performance and algorithm evaluation. The track also welcomes real-world applications of simulation optimization.

In regard to the methodological topic areas of interest, some of the more notable areas are listed below, although this track will not be strictly limited to this list.

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


Track Coordinators: Edward Williams (University of Michigan and PMC), Ernie Lee (Arup), Meng Chao (University of Southern Mississippi), David T. Sturrock (Simio LLC)

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 to present their innovations and successful applications.

For each slot, you have two options: submit a complete paper (strongly recommended for publicity and archival value) or submit only an abstract. Papers are subject to the standard WSC submission timeline and review process and appear in the archival proceedings.  Vendor track abstracts should use the abstract template for submission.  Abstracts that are not peer-reviewed will appear online and in the final program, but not the archival proceedings.

The links for submitting papers and abstracts will be provided when you make your commitment to exhibit.

The submission process is as below: