Study for Intelligent Simulation Framework Structure of Equipment Support System Based ACP-Approach

2013 ◽  
Vol 791-793 ◽  
pp. 1476-1479
Author(s):  
Shou Yu Zhang ◽  
Shi Zhen Guo
Keyword(s):  
Support System ◽  
Simulation System ◽  
Parallel Execution ◽  
Computational Experiments ◽  
Framework Structure ◽  
Simulation Framework ◽  
Simulation Research ◽  
Agent Based ◽  
Intelligent Simulation ◽  
New Framework

Research of wartime equipment support simulation faces complex and great challenges. It is very difficult to describe, design and finish the complex giant equipment support simulation system with the traditional simulation and model methods. Proposing a new framework structure based on ACP (artificial systems and computational experiments and parallel execution) approach to solve the complexity giant simulation of RESS (real world equipment support system). Including agent-based model analysis, computational experiments and decision-making problems and etc and discuss an ESASS (equipment support artificial simulation system) platform framework. The work can provide an actionable guidance to equipment support practice simulation research.

Intelligent Simulation System for Supply Chain Event Management (SCEM)

2010 ◽  
pp. 118-132
Author(s):  
Barin Nag ◽  
Haiying Qiao ◽  
Dong-Qing Yao
Keyword(s):  
Supply Chain ◽  
Simulation System ◽  
Illustrative Case ◽  
Functional Design ◽  
Event Management ◽  
Simulation Framework ◽  
Output Layer ◽  
Intelligent Simulation ◽  
Illustrative Case Study

In this chapter, the authors present an intelligent simulation system for supply chain event management for the purpose of designing and re-engineering the supply chain. The simulation framework mainly composes of component layer, process layer, intelligent execution layer, and output layer. The functional design of the layers is discussed with comments on the contribution of the simulation. Implementation issues are further addressed and an illustrative case study is reported.

scholarly journals Multi-Criteria, Co-Evolutionary Charging Behavior: An Agent-Based Simulation of Urban Electromobility

2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
City Planning ◽  
User Behavior ◽  
Transport Sector ◽  
Simulation Framework ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Charging Station ◽  
Spatio Temporal

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.

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