Keywords

Multi method, modeling, simulation, discrete event, system dynamics, agent based, framework

Abstract

Decisions about Modeling and Simulation (M&S) of Complex Systems (CS) need to be evaluated prior to implementation. Discrete Event (DE), System Dynamics (SD), and Agent Based (AB) are three different M&S approaches widely applied to enhance decision-making of complex systems. However, single type M&S approaches can face serious challenges in representing the overall multidimensional nature of CS and may result in the design of oversimplified models excluding important factors. Conceptual frameworks are necessary to offer useful guidance for combining and/or integrating different M&S approaches. Although several hybrid M&S frameworks have been described and are currently deployed, there is limited guidance on when, why and how to combine, and/or integrate DE, SD, and AB approaches. The existing hybrid frameworks focus more on how to deal with specific problems rather than to provide a generic way of applicability to various problem situations. The main aim of this research is to develop a generic framework for Multi-Method Modeling and Simulation of CS, which provides a practical guideline to integrated deployment or combination of DE, SD, and AB M&S methods. The key contributions of this dissertation include: (1) a meta-analysis literature review that identifies criteria and generic types of interaction relationships that are served as a basis for the development of a multi-method modeling and simulation framework; (2) a methodology and a framework that guide the user through the development of multi-method simulation models to solve CS problems; (3) an algorithm that recommends appropriate M&S method(s) based on the user selected criteria for user defined objective(s); (4) the implementation and evaluation of multi method simulation models based on the framework's recommendation in diverse domains; and (5) the comparison of multi-method simulation models created by following the multi-method modeling and simulation framework. It is anticipated that this research will inspire and motivate students, researchers, practitioners and decision makers engaged in M&S to become aware of the benefits of the cross-fertilization of the three key M&S methods.

Notes

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Graduation Date

2015

Semester

Fall

Advisor

Karwowski, Waldemar

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Degree Program

Modeling & Simulation; Engineering

Format

application/pdf

Identifier

CFE0005980

URL

http://purl.fcla.edu/fcla/etd/CFE0005980

Language

English

Release Date

December 2015

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic

Included in

Engineering Commons

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