Advanced Tutorials Gaming Poster Session
Agent-Based Simulation Healthcare Project Management and Construction
Analysis Methodology Hybrid Simulation Risk Analysis
Aviation Modeling and Analysis Introductory Tutorials Safety Applications
Big Data in Simulation Logistics, Supply Chains, Transportation Scientific Applications
Case Studies MASM: Semiconductor Manufacturing Simulation Education
Complex, Intelligent, Adaptive and Autonomous Systems (CIAAS) Manufacturing Applications Simulation Optimization
Cybersecurity Military Applications Uncertainty Quantification and Robust Simulation
Environment Sustainability and Risk Modeling Methodology Vendor
Financial Risk Management Networks and Communications  

Advanced Tutorials

Track Coordinators: Andrea D’Ambrogio, University of Rome Tor Vergata, Italy; Andreas Tolk, MITRE Corporation

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 visualization, augmented and virtual reality, symbiotic and embedded simulation, 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, UK; Karthik Vasudevan, Amazon

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 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


  • 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
  • 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: Dashi Singham, Naval Postgraduate School; Wei Xie, Rensselaer Polytechnic Institute; Ben Feng, University of Waterloo, Canada; Demet Batur, University of Nebraska-Lincoln

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: Miguel Mujica Mota, HVA – Amsterdam University of Applied Sciences (NL); Michael Schultz, TU Dresden, Germany

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

Big Data in Simulation

Track Coordinators: Abdolreza Abhari, Ryerson University, Canada; Hamdi Kavak, George Mason University

Big data has been one of the most prevalent subjects in information sciences for the last decade. The modeling and simulation community, on the other hand, is just getting involved in the big data trend. Big Data in 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 include:

  • Data-driven simulations
  • Simulation initialization techniques using big data
  • Simulation-generated big data including online social networking services
  • Simulation of databases including massive data sets
  • Big data analytics and generating stochastic data
  • Simulation of algorithms and machine learning methods for processing big data
  • Novel statistical techniques in simulations
  • Machine learning and data mining in simulations
  • Big data management/processing techniques for simulations
  • Advanced data flow techniques for feeding symbiotic simulations
  • Influence of big data in simulation verification and validation
  • Software architectures for big data modeling for simulations
  • Data engineering
  • Ontologies for big data modeling
  • Simulation applications in different fields that use or generate big data
  • Simulation of recommendation systems with big data
  • Simulation of distributed and parallel platforms for processing big data
  • Simulation of massive data mining applications

Case Studies

Track Coordinator:  Fei Chen, Johnson & Johnson and David Sturrock, Simio LLC

The Case Studies Track serves as a multidisciplinary forum for commercial simulation practitioners to share what they have learned modeling real world problems using simulation. The applications are open to all areas including, but not limited to:

• Manufacturing
• Logistics and distribution
• Healthcare
• Mining
• Social and human behavior
• Aerospace
• Food services
• Military
• Data analytics
• Standard implementations

The track will consist of 30-minute presentations, which should include 5-10 minutes for questions and answers. The presentations should focus on a specific problem where simulation was utilized to conduct an analysis and provide recommendations for potential solutions. A two-page extended abstract is required to be submitted for consideration via the WSC submission site. No full length paper is required. The extended abstract should, at a minimum, describe the problem, the simulation methods used, the results, and the impact/benefits of the project. A separate shorter version of the abstract limited to 150 words must also be submitted. The abstracts will be reviewed and those case studies selected for presentation at WSC will have their abstract appear in the final program of WSC and on the WSC Archive website to share what they have learned modeling real world problems. If you are interested in having a relevant panel session in the case study track, you need to submit a two-page extended abstract that describes the panel. A 90-minute panel slot will be allocated to those whose panel proposals have been accepted. Case Study track papers should use the standard template for submission; please obey the two-page length limit.

The submission process is as below:

• August 2, 2019 – Submission deadline for extended abstracts
• August 28, 2019 – Reviews provided to authors.
• September 7, 2019 – Revised abstracts due. Submissions earlier than due date appreciated.
• Mid September 2019 – Editing changes required to meet the formatting guidelines provided to authors
• Late September 2019 – Final version due by the date specified by the editor-in-charge of the abstract

Complex, Intelligent, Adaptive and Autonomous Systems (CIAAS)

Track Coordinators: Saurabh Mittal, MITRE Corporation; Claudia Szabo, U. Adelaide, Australia

The increasing popularity of the Internet of Things, or IoT metaphor emphasizes that heterogeneous systems are the norm today. A system deployed in a netcentric 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.

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. 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 and brings researchers, developers and industry practitioners working in the areas of complex, adaptive and autonomous SoS engineering that may incorporate human as an integral part of SoS operations. This objective covers the following topics:

  • Theory for adaptive and autonomous systems
  • Intelligence-based systems
  • Computational intelligence and cognitive systems
  • Human-in-the-loop systems
  • M&S Frameworks for intelligent behavior
  • Methodologies, tools, and architectures for adaptive control systems
  • Knowledge engineering, generation and management in CIAAS
  • Weak and Strong emergent behavior, Emergent Engineering
  • Complex adaptive systems engineering
  • Self-* (organization, explanation, configuration) capability and collaborative behavior in CIAAS
  • Applications to robotics, unmanned vehicles systems, swarm technology, semantic web technology, and multi-agent systems
  • Net-centric CIAAS
  • Live, Virtual and Constructive (LVC) environments
  • Simulator design for CIAAS systems
  • Modeling tools for CIAAS design
  • 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 to advance the M&S of CIAAS. 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 foundation for resilient intelligent systems, and M&S thereof. Topics related to this objective include, but are not limited to:

  • 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 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 Live, Virtual and Constructive environment
  • 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 environment 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
  • Verification, validation and accreditation of Complexity in SoS
  • Application of Complexity aspects in domain engineering: Financial, Power, Robotics, Swarm, Economic, Policy, etc.
  • SoS Failure due to Complexity


Track Coordinators: Jason Jaskolka, Carleton University, Canada; Sachin Shetty, Old Dominion University; Danda Rawat, Howard University; Kevin Jin, Illinois Institute of Technology

The use of modeling and simulation can have a profound impact on the ability to understand the threat landscape of many of the complex cyber systems that underpin our daily lives. The growth in the number of interconnected physical and cyber systems has resulted in increased interactions and interdependencies and the need for better understanding of attack surfaces in the integrated system. Modeling and simulation provide a cost-effective means to support research, development, refinement, deployment, and evaluation of the next generation of security solutions for preventing, detecting, and recovering from cyber-attacks and failures. The goal of this track is to provide a forum where the academic, commercial, industrial, and government communities can come together to present and discuss advancements in research, tools, techniques, solutions, best practices, and heuristics related to the modeling and simulation of cybersecurity. We encourage submissions related to all aspects of cybersecurity in a modeling and simulation context in a broad spectrum of application areas. Topics of interest include, but are not limited to:

  • Modeling and simulation of cybersecurity with respect to:
    • Discovery and awareness of threats and attacks (broadly construed)
    • Design and development of cybersecurity protocols and schemes
    • Critical infrastructure protection
    • Cyber intelligence and profiling
    • Cyber warfare
    • Insider threats
    • Intrusion detection and prevention
    • Risk assessment and management
    • Systems engineering for security
  • Formal models for cybersecurity simulation
  • Cybersecurity evaluation and assessment approaches
  • Testbeds and experimental infrastructure for cybersecurity simulation
  • Simulation platforms for cybersecurity assessment
  • Hybrid simulations for cyber physical system security
  • Cyber deception and cyber visualization

Environment Sustainability and Risk

Track Coordinators: Elie Azar, Khalifa University, United Arab Emirates; Carol Menassa, University of Michigan

The Environmental Sustainability and Risk track focuses on the use of modeling and simulation to understand the effect of risk and uncertainty on the environment, coupled natural-human systems, and infrastructure, and to evaluate resilient solutions to environmental sustainability challenges. Application areas include ecological systems, natural disasters, renewable resources, sustainable buildings and infrastructure, sustainable manufacturing, and urban planning. We solicit papers presenting new ideas, concepts, models, methods, tools, standards, and applications pertaining to the evaluation and mitigation of risks to achieve sustainability and resiliency in natural and man-made environments. Possible topics include, but are not limited to:

  • Human-environment interaction
  • Ecological systems
  • Natural disasters and their impact on society
  • Human adaptation to climate
  • Renewable resources and related processes
  • Sustainable power grids/smart grids
  • Energy efficient and sustainable urban planning and design
  • Green and robust building design
  • Sustainable and resilient infrastructure
  • Energy/resource efficient manufacturing
  • Environmental modeling, visualization, and optimization
  • Environmental risk assessment and mitigation
  • Decision support and analytics for sustainability
  • Information modeling and interoperability for sustainability applications

Financial Risk Management

Track Coordinators: Jeff Hong, City University of Hong Kong; Jose Blanchet, Stanford University

This track supports the application and the development of stochastic simulation tools and techniques in problems motivated by finance and insurance. Contributions submitted to this track must present a clear motivation in areas such as financial risk quantification, risk management, hedging, portfolio management, credit risk, insurance risk theory and wealth management. In addition, the contribution must clearly answer innovative questions of interest in the areas defined earlier or present novel simulation methodology which can be widely applied to financial problems.


Track Coordinator: Sebastiaan Meijer, KTH Royal Institute of Technology, Sweden; Jayanth Raghothama, KTH Royal Institute of Technology, Sweden

The Gaming track deals with the intersection of games and simulation in application domains such as business, management, entertainment, training, military, and medical sciences. The track focuses on the use of simulation techniques in game design and development. 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.

This track invites papers that demonstrate the application of gaming approaches and technologies, supported by simulation for learning, training, design, planning and decision making. The track also encourages papers that address the use of modeling and simulation techniques in game design and development. In particular focus is the use of interactive techniques and visualization approaches in simulation, such as Augmented and Virtual Reality. Topics include, but are not limited to, the following:

  • Gaming as a method in simulation projects
  • Game design approaches, methodologies, and techniques (prototyping, playtesting, evaluation, risk analysis)
  • Game architectures and environments for learning, training and decision support
  • Assessment and evaluation of games
  • Games with simulation content for Design, Policy Making and Decision Support
  • Validation of simulation with gaming methods.
  • AI in Games
  • Multi-agent or behavioral simulation in game environments (Intelligent agents, Agent Technologies, ABMs in game engines and game development)


Track Coordinators: Maria Mayorga, NC State University; Xiaolan Xie, Ecole Nationale Supérieure des Mines de Saint Etienne, France; Masoud Fakhimi, University of Surrey, UK; Jie Song, Peking University, China

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: Tillal Eldabi, Brunel University, UK; Antuela Tako, Loughborough University, UK; David Bell, Brunel University, UK

The Continuous and 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.

Introductory Tutorials

Track Coordinators: Gregory Zacharewicz, IMT Mines Alès, France; Antonella Petrillo, U. Cassino e del Lazio Meridionale, Italy

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 and software tools.

Logistics, Supply Chain Management, Transportation

Track Coordinators: David Goldsman, Georgia Institute of Technology; Markus Rabe, Technische Universität Dortmund, Germany

The nature of highly dynamic and complex networks of supply, intralogistics, and distribution leads to decreasing transparency of the processes, while at the same time failure risks are increasing. Therefore, managers who are responsible for supply chain management and logistics require effective tools to provide credible analysis in this dynamic environment. In order to facilitate the discussion of the best applications of simulation in this area, the LST track includes papers in logistics simulation, supply chain simulation, and simulation for planning, analyzing, and improving transportation in the wide scope from the detailed intralogistics view 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
  • Lean 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

Modeling and Analysis of Semiconductor Manufacturing (MASM)

Track Coordinators: John Fowler, Arizona State; Lars Mönch, University of Hagen, Germany; Tae-Eog Lee, KAIST, Korea

Manufacturing Applications

Track Coordinator: Guodong Shao, U.S. National Institute of Standards and Technology; Christoph Laroque, WH Zwickau, Germany; Loo Hay Lee, National University of Singapore

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

Military Applications

Track Coordinator: MAJ Nathan Bastian, Army Cyber Institute, U.S. Military Academy; COL Andy Hall, Army Cyber Institute, U.S. Military Academy

The Military Applications track is interested in papers that describe the application of modeling and simulation methods to challenges in the military, national security and homeland defense domains. Application areas include: battle management command and control, air and missile defense, campaign analysis, land and expeditionary warfare, air warfare, logistics, reliability and maintainability, experimentation, measures of merit, test and evaluation, analysis of alternatives, wargaming, assessments, CBRNE defense, infrastructure analysis, protection and recovery, homeland security and civil support, information and cyber operations, electronic warfare, command and control, intelligence, surveillance and reconnaissance, space operations, maritime operations, casualty estimation and force health protection, manpower and personnel, readiness and training, operational energy, cost analysis, decision analysis, special operations and irregular warfare, and so on. Topics of special interest include, but are not limited to

  • Challenges and innovations for representation and implementation of robotic swarms
  • Cybersecurity operations and cyber threats
  • Social media
  • Hardware-in-the-loop simulations
  • Future human-robot operations
  • Future platforms and weapons prototyping
  • Synthetic environments
  • Instrumentation and sensors
  • Complex behaviors of semi-automated forces
  • Electronic warfare
  • Mass casualty triage
  • Medical operations
  • Behaviors related to human body and wounds
  • Range systems
  • Automatic scenario planning and exercise data management
  • Multi-resolution models

Papers investigating an innovative use of cloud technologies and services, gaming technology, mixed reality (MR) technology, artificial intelligence technology, big data technologies, and networking technology for military, national security and homeland defense applications are also welcome!

Modeling Methodology

Track Coordinators: Gabriel Wainer, Carleton University, Canada; Richard Fujimoto, Georgia Institute of Technology; Olivier Dalle, University of Nice, France

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

Networks and Communications

Track Coordinators: Stenio Fernandes, Federal University of Pernambuco, Brazil; Jason Liu, Florida International University

The Networks and Communications track focuses on technologies for modeling and simulating computer and communication networks, networked systems and applications, wireless and mobile communications, and the like. Topics of interest include, but are not limited to, the following:

  • Network design and analysis
  • Network dependability
  • Distributed and networked applications and systems
  • Future internet architecture, clean-slate network design,
  • Software-Defined Networking (SDN)
  • Network Functions Virtualization (NFV)
  • Wireless and mobile networks
  • Cloud, Fog, and Data Center networking
  • Cybersecurity
  • Traffic modeling and analysis
  • High-performance network modeling techniques
  • Large-scale network simulation
  • Network simulation tools and software
  • Network emulation, real-time simulation, online simulation, symbiotic simulation
  • Training and education


Poster Session

Track Coordinators: Cristina Ruiz Martín, Carleton University; Masoud Fakhimi, University of Surrey, UK; Guilia Perdrielli, Arizona State University

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. To be considered, submitted manuscripts should follow the standard template, and should not exceed the 2 pages limit. Extended abstract submissions are encouraged in all areas of modeling and simulation as mentioned in the Call for Papers. In particular, we are seeking contributions within, but not restricted to, the following areas:

  • Simulation Methodology, Theory and Philosophy
  • Hybrid Simulation and Hybrid System Modeling
  • Simulation-based Optimization
  • Environment and Sustainability Applications
  • Simulation for logistics, Supply chain Management and Transportation
  • Simulation Education
  • Simulation Languages, Tools, and Environments
  • Numerical Simulation and Optimization as Applied to Business and Industry
  • Use of Modeling and Simulation in the Area of Computer Security
  • Machine Learning, Artificial Intelligence, Image/Video Compression/Processing and Robotic Vision, real time and embedded systems, and Multimedia Applications and Systems
  • Any Aspect of Modeling and Simulation related to the Military
  • Modeling, Analysis and Simulation of Telecommunication Systems
  • Web-based Modeling and Simulation
  • High-performance Computing and Simulation
  • Network/Internet Traffic Modeling and Workload Characterization
  • Simulation of Clusters, Grids and Wireless Systems
  • Modeling and Simulation of Real-Time and Embedded Systems
  • Parallel and Distributed Simulators and Simulation Techniques
  • Modeling and Simulation in the area of Neural Networks

Project Management and Construction

Track Coordinators: Ming Lu, University of Alberta, Canada; Fei Dai, West Virginia 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

For this track, we will accept short 5-page papers; longer versions can subsequently be submitted to journals in project management and construction.

Risk Analysis

Track Coordinators: David Poza, University of Valladolid, Spain; Sam Savage, Stanford University

Risk analysis is evolving from qualitative approaches such as heatmaps and risk registers to quantitative models that generally require Simulation. Topics addressed by this track include:

  • Classes of Risk Modeling and Simulation
  • Aggregating simulation results across diverse platforms
  • Simulating rare risk events
  • Risk monitoring and control
  • Presenting simulation outputs to diverse stakeholder including the public
  • Stochastic optimization methods for risk mitigations
  • Simulating environmental risk due to climate change, earthquake, asteroid strike, etc.
  • Simulating infrastructure risk, such as pipelines, bridges, power transmission lines

Safety Applications

Track Coordinators: John Shortle, George Mason University; Amarnath Banerjee, Texas A&M University; Kevin Taaffe, Clemson University

The Safety Applications Track seeks papers related to the evaluation of system safety via simulation. Safety-critical systems are those whose failure may cause significant harm to people, property, or the environment. Because of the potential high consequence of failure, such systems are often designed with extremely low probabilities of failure. The Safety Applications Track welcomes papers in all safety-related application areas including ground transportation, air transportation, health care, medical systems, construction, energy, environment, autonomous systems, military, and so forth. Examples of applications may include high-consequence events, such as aircraft collisions, low-consequence events, such as injury from a drone strike, and the spread of disease/infection influenced by the surrounding environment. Appropriate simulation methodologies (in addition to discrete event, agent based, and system dynamics) could include rare-event simulation, event/fault trees, and hybrid simulation methods.

Scientific Applications

Track Coordinators: Esteban Mocskos, University Buenos Aires, Argentina; Sergio Nesmachnow, University of the Republic, Uruguay

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 Education

Track Coordinators: Saikou Diallo, Old Dominion University; Mamadou Seck, Old Dominion University

The focus of this track is training and educating the next generation of scientists, engineers, artists, humanists and social scientists. Simulation is a staple of scientific inquiry and its applications are wide-ranging. However, in order to make it truly ubiquitous, it is essential to train and educate simulation professionals to engage and apply their knowledge to various areas. It is also imperative to engage students and professionals in every domain to incorporate simulation in their daily activities.

The Simulation Education track is seeking papers and panels from professionals in all disciplines including but not limited to engineering, sciences, arts, humanities and social sciences to share experiments, lessons learned, projects, methods, tools and case studies on how to train and educate students, scientists, and scholars at all levels and of all kinds to adopt and incorporate simulation in their work.

Simulation Optimization

Track Coordinators: Susan Hunter, Purdue University; Peter Salemi, MITRE Corporation; Juergen Branke, Warwick Business School, UK

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

Uncertainty Quantification and Robust Simulation

Track Coordinators: Henry Lam, Columbia University and Eunhye Song, The Pennsylvania State University

The uncertainty quantification and robustness track aims to cover methodological techniques 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 misspecifications, based either on data or subject domain knowledge. Topics of interest include, but are not limited to, the following:

  • Criteria for input uncertainty quantification
  • Efficiency of uncertainty quantification methods
  • Robustness in input modeling and selection
  • Model risk quantification
  • Uncertainty in model calibration and validation
  • Robust simulation optimization
  • Robustness against simulation logic misspecifications
  • Sensitivity analysis on input parameters or distributions
  • Statistical methods for uncertainty quantification


Track Coordinators: Edward J. Williams, University of Michigan & PMC; Miguel Mujica Mota, HVA – Amsterdam University of Applied Sciences, Netherlands

The Vendor Track provides an opportunity for companies that market modeling and simulation technology and services to present their innovations and successful applications. The track is open only to companies that have paid for exhibit space at the conference.  For each reserved booth, vendors get a 45-minute time slot in the track.

For each slot, you have two options: submit a complete paper or submit just 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:

  • August 2, 2019 – Submission deadline for extended abstracts
  • August 28, 2019 – Reviews provided to authors.
  • September 7, 2019 – Revised abstracts due. Submissions earlier than due date appreciated.
  • Mid September 2019 – Editing changes required to meet the formatting guidelines provided to authors
  • Late September 2019 – Final version due by the date specified by the editor-in-charge of the abstract