Publication Date

2020

Document Type

Dissertation/Thesis

First Advisor

Wang, Ziteng

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Industrial and Systems Engineering

Abstract

Routing problems, such as traveling salesman problem, vehicle routing problem, and their variants, have been extensively studied in operations research because of their wide application in transportation and logistics. In this thesis, we consider routing problems in a road network of which the traveling conditions change over time and sometimes are uncertain. Such problems can arise in humanitarian logistics, resident evacuation, and emergency resource delivery after severe weather events and natural disasters. We provide a methodology to support routing decisions including route planning with limited information of the network conditions and route updating as new information becomes available. The dynamic network condition is modeled by defining a time-varying speed reduction factor. We update the estimation of this speed reduction factor by integrating prior estimation with the latest travel data from the vehicles in a Bayesian inference framework. The Ant Colony Optimization method is used to find the optimal routes in the planning phase and updating phases. Two case studies show the effectiveness of the proposed methodology for both the single route and multiple route problems and the necessity to consider dynamic uncertain network conditions.

Extent

98 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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