# ESM — European Simulation and Modelling Conference

- **Submission deadline**: 2020-06-25
- **Notification date**: 2020-08-25
- **Conference date**: 2020-10-21
- **Location**: Toulouse, France
- **Conference Partner Index**: 51.2/100 (ranked #1344, confidence 0.45, algorithm 1.1) — how this is computed: https://www.myhuiban.com/ranking
- **Trackers**: 0
- **Attendees**: 0
- **Canonical page**: https://www.myhuiban.com/conference/3196

## Call for papers

General Simulation Methodology and Tools 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 Monte Carlo 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 Queueing Models Queueing phenomona are omnipresent, for example work in progress waiting at a workstation, vehicles in traffic jams, and packets waiting to be transmitted. Developing a queueing model and analyzing it analytically, numerically, or via simulation, has been very effective in the performance analysis of various systems. This track encourages papers addressing analytic, numerical and simulation studies of queueing phenomena. 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 IoT and Smart Industry" (Internet of Things & Industry 4.0) The use of Smart-IoT in different domains (Smart Manufacturing Systems, eHealth, smart-agriculture, etc.), imposes new challenges in design and verification of such embedded systems. These smart-components are often software dominated. The optimization and deployment of the software part become a complex task. In addition, and for performance purpose, the need to implement certain functions as hardware accelerators (IP : Intellectual Proprieties) is highly recommen

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