Introductory tutorial: Agent-based modeling and simulation

Macal,

doi:10.1109/wsc.2011.6147864

Cited by 61 publications

(57 citation statements)

References 28 publications

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“…Kenley et al (2014) reviewed ABS approach in the MBSE context and they have defined a dynamics model of an agent as shown in the Figure 2. Thus, the basic components of an ABS can be identified as follows (Macal & North, 2014): 1. Agent Attributes: These define the basic characteristics of an agent.…”

Section: Understanding the Link Between Sysml And Agent-based Simulationmentioning

confidence: 99%

Minimum SysML Representations to Enable Rapid Evaluation using Agent‐Based Simulation

Maheshwari

Raz

Dervisevic

et al. 2018

INCOSE International Symp

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The changing operational requirements and demands for new capabilities, often makes it necessary for systems architects to make substantial changes in a system's architecture. However, the traditional systems engineering processes advocate finalization of architecture at early stages of the design process with little or no change at the later stages of the design. The simulation development is often done towards the end of the design phase and thus, the traditional systems engineering approaches do not support a rapid architecture evolution. In this paper, we propose a Model‐Based Systems Engineering (MBSE) process to facilitate rapid evaluation of changes in a system architecture and/or design artifact for complex systems. This process specifies the minimum set of information that needs to be included in system architecture using SysML diagrams with traceability between the diagrams and agent‐based simulation (ABS) models of a complex system. We demonstrate this SysML‐driven analysis approach to perform a rapid evaluation of evolving system architectures using a NASA‐sponsored project to analyze ab initio architectures for the National Airspace System. We also demonstrate how the proposed approach enables early‐on investigation during the architecture development whether an architecture will yield the desired operational benefit.

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Section: Understanding the Link Between Sysml And Agent-based Simulationmentioning

confidence: 99%

Minimum SysML Representations to Enable Rapid Evaluation using Agent‐Based Simulation

Maheshwari

Raz

Dervisevic

et al. 2018

INCOSE International Symp

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“…Reffering to the supply chainthe individual chain participants (companies, manufacturers, wholesalers and retailers) can be treated as agents who have their own goals and skills, and their common goal is to produce and deliver a product to a specific customer (http://www.anylogic.com). Agent-Based Simulation is discussed in more detail in (Kim & Robertazzi 2006); (Macal & North 2013). There are also numerous articles dedicated to agent modeling and multi-agent modeling in the transport and supply chains (Balbo & Pinson 2005); (Bocewicz et al 2013).…”

Section: The Complexity Of the Supply Chain Issuementioning

confidence: 99%

A way of simulation transport processes and distrubances in supply chain

Hoffa-Dąbrowska

Pawlewski

2016

RLP

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The paper presents a description of how to model the supply chain using simulation software. In order to make the best representation of reality, not only the route and the lorry's speed are taken into account, but also the presence of various types of disturbances, like the occurrence of severe weather conditions or the inclusion of the driver's breaks, according to the applicable regulations. The purpose of this article is to demonstrate how to model the disturbance and to present benefits of using of simulation programs to plan a route of transport.

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“…• Agents' environment For further details refer to Macal and North (2011) and North and Macal (2007).…”

Section: Modeling Of Supply Chains Using Multi-agent Systemsmentioning

confidence: 99%

Structural mapping of public distribution system using multi-agent systems

Ambekar

Kapoor

Mehta

2015

Business Process Management Journal

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Purpose – The purpose of this paper is to develop a framework for mapping the Indian Public Distribution System (PDS) using multi-agent system (MAS). The entire PDS supply chain from purchase to the distribution is mapped in detail by integrating stages of PDS supply chain. Design/methodology/approach – Literature related to PDS, food grain supply chain (FGSC) and MAS is reviewed and critically assessed. Based on this a framework is proposed which will help in improving functioning of PDS. Findings – The PDS has many shortcomings arising from its complex structure and practices which are used to implement it. The authors propose an MAS to model it in which each entity will be modelled as an agent. The authors propose two stages of supply chain. First stage models the processes from procurement to storage of food grain and second stage model the distribution process. Practical implications – This paper will be of interest to the policy makers and decision makers involved in the PDS by providing the shortfalls in the system and also suggesting a method to model the PDS based on practices of food supply chains. Originality/value – This paper provides the decision makers in the PDS, a framework to model and assess the entire supply chain. This will help them in effective implementation of the PDS and also improve in the areas of concerns which are pointed the study.

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Introductory tutorial: Agent-based modeling and simulation

Cited by 61 publications

References 28 publications

Minimum SysML Representations to Enable Rapid Evaluation using Agent‐Based Simulation

Minimum SysML Representations to Enable Rapid Evaluation using Agent‐Based Simulation

A way of simulation transport processes and distrubances in supply chain

Structural mapping of public distribution system using multi-agent systems

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