Modelling Methodology

Continuous, discrete and hybrid simulation methodology, Simulation environments, Multi-paradigm simulation, Simulation uncertainty, Simulation visualisation, Integration of simulation and geographical information systems, Object-oriented programming and Languages, Multi-paradigm Languages, Software comparisons. Numerical Methods for Simulation, Mathematical Analysis in Simulation, Parallel Simulation Methodology, Discrete Event Simulation, Simulation Fidelity and Performance Evaluation, Advanced Training and Simulation Concepts for Education, Multiparameter Sequential Optimization Methods in Simulation, Verification, Validation, and Control in Complex Systems Simulation, Distributed and Parallel Systems Simulation, Combined Continuous and Discrete Event Models, Symbol Analysis and Manipulation of Equation-Based Models, Simultaneous vs Modular Simulation Methods, Standardization Issues

Object Orientation and Re-Use

Object-Oriented Modelling Languages, Modularity, Model Structuring, Inheritance, Model Re-use, Organization of Model Libraries

Tools

Simulation Tools, Statistical Output Evaluation Tools, Optimization Tools, Special Purpose Simulation Languages and Tools, Simulator Development Environments, Interfaces for Coupling with External Tools. Adapting tools to comply with the ISO 26262 and MISRA standards.

Random simulation and applications

Monte Carlo, Quasi Monte Carlo and Latin methods, random numbers, stochastic processes. generation, multivariate simulation, simulation in applied area (mechanics, biology, astronautics and aeronautics,economy and finance, computer science) with oriented industrial applications.

Discrete Simulation Modeling Techniques and Tools

Simulation Modeling Techniques, namely those concerned about discrete event simulation, usually play a crucial role in teaching and learning approaches to simulation. Nevertheless the classical simulation approach would be used to introduce students to the area of simulation – Event World View, Process World View or Activity World View, there is a permanent difficulty to focus on the basics of simulation, to focus on the foundations of simulation. In fact, in most cases, the need for some background on computer programming will tend to neglect those matters and concentrate on syntax details of some programming language rather than on a full comprehension of simulation basic concepts. This track is then intended to concentrate on new developments as far as simulation modeling techniques is concerned, including the use of graphical approaches to simulation modeling and also to the automatic generation of simulation programs. Contributions based on Event Scheduling approaches, Activity Cycle Diagrams approach or Process Flow approaches are most welcome. Contributions related to educational concerns but also contributions related to industrial applications are encouraged.

The following topic areas within this track on Discrete Simulation Modeling Techniques and Tools (although this list should not be treated as exclusive), will be object of interest:

• Discrete Event Simulation
• Event Scheduling
• Activity Cycle Diagrams
• Process Flow
• Visual Modeling Tools
• Visualization and Animation Tools
• Business Process Modeling
• Simulation Methodology
• Simulation Education
• Simulation Industrial Applications
• Flowchart Simulation
• Automatic Generation of Simulation Programs
• Customization of Software for Discrete Event Simulation

Simulation and AI

AI Based Simulation Languages, Special Architectures, Graphical Simulation Environments and Simulation Software Tools, Intelligent Simulation Environments, Parallel Processing Environments for Simulation, User Friendly Software Tools, Advanced Man-Machine Interfaces, Graphical Model Editors, Browsing Facilities, Database Management of Models and Results, Architecture of Modelling and Simulation Environments, Abductive Reasoning Logic Tools.

AI and Expert Systems

Expert Controllers and Genetic Algorithms in Simulation, Knowledge Based Simulation Tools, AI and Expert Systems in Simulation.

AI and Neural Networks

Classification, Data analysis, Fault tolerance, Forecasting, Knowledge acquisition, Economics and Finance, Planning, Pre-treatment of data, Process control, Robotics, Speech and image recognition, Web intelligence, involving methodologies such as: Hybrid systems (GA, fuzzy, symbolic representation), Methods or tools for evaluating ANN performance, Reinforcement Learning, Simulation tools (research, education, development), Neural nets for simulation: modelling of parts (components) of the system simulated by neural networks, evaluation of simulation models using neural nets, decision support in simulation models by neural nets; Simulation of neural nets: systems of pre-designed neural networks, techniques and tools for simulation and programming of neural networks.

AI and fuzzy Systems

Fuzzy Qualitative simulation, fuzzy rules and fault models. Classification, Data analysis, Fault tolerance, Forecasting, Knowledge acquisition, Economics and Finance, Planning, Pre-treatment of data, Process control, Robotics, Speech and image recognition, Web intelligence, involving methodologies such as: Hybrid systems (GA, fuzzy, symbolic representation), Methods or tools for evaluating ANN performance, Reinforcement Learning, Simulation tools (research, education, development).

Agent-Based Simulation

Agent Based Simulation is an inter-disciplinary area which brings together researchers from different areas, the social simulation and the Multi-agent Systems. The focus of Agent Based Simulation is on simulating and organization social behaviours in order to understand real social systems via the development and testing of new concepts.

The following topic areas (although this list should not be treated as exclusive), will be object of interest:

• Agent-based simulation techniques and methodologies
• Agent Architectures, Model Specification and Languages
• Decision making and Strategies
• Game Theory and Fuzzy logic for agent-based modeling
• Discrete-event simulation in Multi-Agent Systems
• Multi-Level Simulation and Emergence
• Simulation toolkits and frameworks
• Applications in Ecology and Environment, Psychology, Cognitive Science and AI, Economics and Market Systems, Business Process Management, Industry, Manufacturing and Logistics and Transport and Healthcare with the emphasis on simulation and modeling
• Agent-based modeling (ABM) within geographical systems

The aim of this track is to allow the debate on emerging issues, gathering the scientific community researching in these areas. This workshop is a forum for discussion and presentation of new contributions on Agent-based simulation

Thus, it is intended:
• to identify the critical points of the use of Agent-based simulation as well as processes and the areas where is needed an urgent action;
• to present and discuss new approaches, trends and innovative aspects of the Agent-based simulation;
• to promote the use of Agent-based simulation and to explore ways to overcome resistance to change;
• to analyze the level of use of Agent-based simulation in Europe and to compare with the world situation.

With this track it is expected that the scientific community gets some
directions from what has been done and what can be done by motivating the
researching and the search for new solutions in the area of Agent Based Simulation

Simulation and Optimization

The aim of this track is to provide a forum for high quality research on simulation and optimization problems. Plenty of hard problems in a huge variety of areas, including logistics, network design, bioinformatics, engineering, business, etc., have been tackled successfully with simulation and optimization approaches. An entire decade passed from the promissory initial contribution for the “Wedding Optimization and Simulation” and it will be an important opportunity to perform an overview over the past and discuss the new trends to the future.

Simulation optimization is a promising field of research, used in practical simulation applications and being incorporated into simulation software tools. This track is a forum for discussion and presentation of new contributions and also an overview of simulation optimization, but with an emphasis on problems with discrete decision variables.

The Simulation and Optimization track at ESM invites original and unpublished contributions in any topic concerning applications of simulation for all kinds of optimization problems. See the list of suggested (but not limited to) topics at:

• Applications of simulation to optimization problems
• Theoretical developments in simulation and optimization
• Neighbourhoods and efficient searching algorithms
• Variation operators for stochastic search methods
• Insight into problem characteristics of problem classes
• Comparisons between different (also exact) techniques
• Incorporation of optimization Packages / Toolkits / Toolboxes in Simulation Software
• Commercial software packages

High Performance and Large Scale Computing

This track invites contributions on efficient Modelling and Simulation Algorithms and Computer-intensive Simulation Projects on High-performance Large Scale Computers and Distributed Platforms. Methods and techniques for parallel simulation (scheduling, synchronisation, load balancing), Performance of parallel and distributed simulation (experimental and comparative studies, performance models, benchmarks), High Level Architecture (HLA) and related standards (time management, model semantics, implementation issues), High Performance and Large Scale Systems for Computational Science (biological, chemical, physical, etc.) Application of parallel and distributed simulation (computer systems, manufacturing systems, etc.), Parallelisation of simulations (numerical methods, (Quasi-Monte-Carlo simulation), Simulation in Cluster, Multicluster, and Grid Computing, Simulation in Pervasive and Ubiquitous Computing (wireless, mobile, wearable, invisible), Parallel Processing with Games Machines, Exaflop Computing.

Simulation in Education and Graphics/Data Visualization Simulation

This track covers; Simulation and e-learning, - Role Strategies) Management Games, Simulation with "man in the loop", Virtual Reality Systems, Realistic Presentation of Simulation, Results, Simulation for Training and Education, Web-based Simulation, Multi-site Group Simulation, Special Purpose Simulation Languages and Tools, Simulation Environments, Simulator Development Environments, Visual Modelling Tools, Multimedia, Visualization and Animation Tools, Interfaces for Coupling with External Tools, Data Models Visualization. Visualization algorithms and techniques, Volume visualization, Information visualization, Multiresolution methods, Modelling techniques and Interaction techniques and architectures

Simulation in Environment, Ecology and Marine Biology

The main goal is to enhance the trans-disciplinarity and to facilitate contacts and dialogs between computer scientists and specialists of Environmental Sciences. Since 10 years the modelling process took benefits from recent (and less recent) techniques of computer science : Object-Oriented Languages, Discrete Event Simulation, Concepts of Agent and Actor, Fuzzy Logic, UML, model - GIS interface, Web-based simulation, environment management, predictive models of forest growth, fishing, climate and other biological processes. Papers dealing with ecological modelling (in a wider sense) are welcome in the areas of: Applications: Environment managing, Waste managing, Ecosystem dynamics (terrestrial and oceanographic ecology) Population dynamics (diseases & epidemics, changes in biodiversity, genome, predator-prey relationships, fishing...), Population behaviour, Individual behaviour, involving methodologies such as: Artificial Intelligence, Distributed Interactive Simulation, High-Performance Computing, Languages, Modelling Techniques, Simulation Methodologies & Tools, Synthetic Environment, Virtual Reality, Petri nets, DEVS and Bond Graphs. Modelling and simulation have an important role in structuring biological, medical and ecological systems. The intrinsic complexity and non-linearity of these types of systems need continuous and discrete simulation methodology, soft computing methodology in order to handle the different degrees of uncertainty, as well as virtual reality methodology describing the time and space dependent complexity.
Marine biology simulation covers the simulation and modelling in Microbiology, Fisheries and Aquaculture, Environmental marine biology, Deep-sea ecology, Ichthyology, Marine mammology and Marine ethology.

Simulation in Biological Systems and Medicine

Topics are biological systems, medical systems and ecosystems with the domain specific topics such as molecular modelling, genetic algorithms in biosystems, fuzzy sets and neural nets in biosystems, physiology, cardiology, anesthesia, cancer, circulatory system, respiratory system, renal system, biomechanics, agricultural production, simulation of global change, ecotechnology and eco-engineering, GIS, population dynamics, etc Simulation of Patient Care,Quality of Service, Hospital Logistics, Simulation of Disease Proliferation, Virtual Reality in Surgical Procedures, Simulating Biological Phenomena and Organs, Simulation as a Tool for Diagnosis, Simulation of Emergency Procedures (Disaster Gaming), General Medical Simulations, Pharmacometric Modelling, Physiological Simulations

Analytical and Numerical Modelling Techniques

Contributions based on exact and approximate methods as well as applications are encouraged but not restricted to the following topics: Techniques and Algorithms, Stochastic Petri Net Models, Queuing Systems and Network Models, Markov Models, Performance Optimization, Stochastic Process Algebras, Stochastic Precedence Graphs, Bounds and Theoretical Properties, Interconnection Networks, Evaluation Studies of Analytical and Numerical Modelling, Computer Systems, Manufacturing Systems, Workflow Management Systems, Communication Systems (LANs and Distributed Systems, ATM Switches, Mobile Radio,...), Transmission Line Matrix Modelling (TLM), Workload modelling and Characterisation, Operating Systems, Client-Server Systems, Multimedia Systems, Measurements and Hybrid Techniques, Software Performance and Software Tools for Analytical and Numerical Modelling.

Web Based Simulation

Web-based Simulation Environments (WSE), Web-based Distributed Interactive Simulation (WDIS) Sharing and reuse of simulation models and tools in WSE , Techniques and Standards for model integration, Communication interoperability in WSE and WDIS, WSE and WDIS applications to education, training and learning. , Simulation visualization/animation in WSE and WDIS, Web-based Distributed Simulation (distributed modelling via the Web, Java based, Federated, and so on).

Cloud Based Simulation

This track covers, Cloud-based execution of simulation tools; Simulation of complex cloud environments; Cloud computing for high-availability / fault-tolerant simulators; Performance and cost evaluation of cloud-based simulation; Novel service models and applications for cloud-based simulations; Privacy, security and trust issues in cloud-based simulation and Mobile cloud computing and simulation

Physics modelling and Cosmological Simulation

Detailed computer simulations are a powerful tool to study one of the biggest challenges for theoretical cosmology: How did the galaxies we see in the universe today form out of the small fluctuations in matter density that were present in the primordial universe? Having carried out the largest cosmological simulations ever, scientists in astrophysics are able to follow the hierarchical galaxy formation process with unprecedented accuracy and detail, allowing new theoretical insights into dark matter dynamics, and novel tests of the cold dark matter theory for galaxy formation. Simulations in this area, at present can be categorized under: The Millenium Simulation, Galaxy Formations Simulation, First Objects, Mock Catalogues, Dark Matter Halos, Intergalactic Medium, Semi-Analytical Modelling and Hubble Volume Simulation, Star Formation