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Workflow analysis for self-Adaptive agent-based simulation model

In real-life environment, 80% of business processes are dynamic whereby each process is dependent on individual conditions of execution and at the same time contains a large amount of parameters that makes them difficult to model. A self-Adaptive, agent-based simulation model for dynamic processes e...

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Main Authors:	Loo, Y.L., Tang, A.Y.C., Ahmad, A., Mustapha, A.
Format:	Conference Paper
Language:	English
Published:	2017
Subjects:	Multi agent systems
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id	my.uniten.dspace-3953
record_format	dspace
spelling	my.uniten.dspace-39532018-12-10T08:15:49Z Workflow analysis for self-Adaptive agent-based simulation model Loo, Y.L. Tang, A.Y.C. Ahmad, A. Mustapha, A. Multi agent systems In real-life environment, 80% of business processes are dynamic whereby each process is dependent on individual conditions of execution and at the same time contains a large amount of parameters that makes them difficult to model. A self-Adaptive, agent-based simulation model for dynamic processes enables reduction of costs, resources and efforts in designing new models. This paper presents a workflow for modelling dynamic processes that consist of key parameters needed for the design and refinement of the simulation model, which are data collection and data analysis. Three dynamic processes are chosen as case studies; crime investigation, new student registration, and transportation requests processes. The workflow of each case study is analyzed using cross-case analysis, directed approach, and grounded theory. The findings showed similarity of key parameters shared by three dynamic processes and thus required to refine the self-Adaptive agent-based simulation model. © 2016 IEEE. 2017-11-01T05:56:31Z 2017-11-01T05:56:31Z 2017 Conference Paper 10.1109/ISAMSR.2016.7809996 en 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016 6 January 2017, Article number 7809996, Pages 16-21
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
language	English
topic	Multi agent systems
spellingShingle	Multi agent systems Loo, Y.L. Tang, A.Y.C. Ahmad, A. Mustapha, A. Workflow analysis for self-Adaptive agent-based simulation model
description	In real-life environment, 80% of business processes are dynamic whereby each process is dependent on individual conditions of execution and at the same time contains a large amount of parameters that makes them difficult to model. A self-Adaptive, agent-based simulation model for dynamic processes enables reduction of costs, resources and efforts in designing new models. This paper presents a workflow for modelling dynamic processes that consist of key parameters needed for the design and refinement of the simulation model, which are data collection and data analysis. Three dynamic processes are chosen as case studies; crime investigation, new student registration, and transportation requests processes. The workflow of each case study is analyzed using cross-case analysis, directed approach, and grounded theory. The findings showed similarity of key parameters shared by three dynamic processes and thus required to refine the self-Adaptive agent-based simulation model. © 2016 IEEE.
format	Conference Paper
author	Loo, Y.L. Tang, A.Y.C. Ahmad, A. Mustapha, A.
author_facet	Loo, Y.L. Tang, A.Y.C. Ahmad, A. Mustapha, A.
author_sort	Loo, Y.L.
title	Workflow analysis for self-Adaptive agent-based simulation model
title_short	Workflow analysis for self-Adaptive agent-based simulation model
title_full	Workflow analysis for self-Adaptive agent-based simulation model
title_fullStr	Workflow analysis for self-Adaptive agent-based simulation model
title_full_unstemmed	Workflow analysis for self-Adaptive agent-based simulation model
title_sort	workflow analysis for self-adaptive agent-based simulation model
publishDate	2017
_version_	1644493581547732992
score	13.222552

Workflow analysis for self-Adaptive agent-based simulation model

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