Doctoral Dissertations

Keywords and Phrases

Adaptive agents; Contingency basing; Model based systems engineering

Abstract

"This research investigates the use of adaptive agents and hybridization of those agents to improve resource allocation in dynamic systems and environments. These agents are applied to contingency bases in an object oriented approach utilizing Model-based Systems Engineering (MBSE) processes and tools to accomplish these goals. Contingency bases provide the tools and resources for the military to perform missions effectively. There has been increasing interest in improving the sustainability and resilience of the camps, as inefficiencies in resource usage increases. The increase in resource usage leads to additional operational costs and added danger to military personnel guarding supply caravans.

The MBSE approach alleviates some of the complexity of constructing a model of a contingency base, and allows for the introduction of 3rd party analysis tools through the XML metadata interchange standard. This approach is used to create a virtual environment for the agents to learn the system patterns and behaviors within the system. An agent based approach is used to address the dynamic nature of base camp operations and resource utilization. , helping with extensibility and scalability issues since larger camps have a very high computation load. To train the agents to adjust to base camp operations, an evolutionary algorithm was created to develop the control mechanism. This allows for a faster time to convergence for the control mechanisms when a change is observed. Results have shown a decrease in resource consumption of up to 20% with respect to fuel usage, which will further help reduce base costs and risk"--Abstract, page iii.

Advisor(s)

Corns, Steven

Committee Member(s)

Cudney, Elizabeth A.
Pernicka, Hank
Smith, Brian Keith
Long, Suzanna, 1961-
Kinnevan, Kurt

Department(s)

Engineering Management and Systems Engineering

Degree Name

Ph. D. in Systems Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2014

Pagination

ix, 101 pages

Note about bibliography

Includes bibliographical references (pages 95-100).

Rights

© 2014 Dustin Scott Nottage, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Intelligent agents (Computer software)
SysML (Computer science)
Contingency theory (Management)
Logistics -- Management
Combat sustainability (Military science)

Thesis Number

T 10617

Electronic OCLC #

902735445

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