Graduation Year

2017

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Industrial and Management Systems Engineering

Major Professor

Bo Zeng, Ph.D.

Co-Major Professor

Kingsley A. Reeves, Jr., Ph.D.

Committee Member

Alex Savachkin, Ph.D.

Committee Member

Qiong Zhang, Ph.D.

Committee Member

Dan Shen, Ph.D.

Keywords

Approximation, Robust Optimization, Bi-level Programming, Scheduling, Network Design

Abstract

Transportation system is one of the key functioning components of the modern society and plays an important role in the circulation of commodity and growth of economy. Transportation system is not only the major influencing factor of the efficiency of large-scale complex industrial logistics, but also closely related to everyone’s daily life. The goals of an ideal transportation system are focused on improving mobility, accessibility, safety, enhancing the coordination of different transportation modals and reducing the impact on the environment, all these activities require sophisticated design and plan that consider different factors, balance tradeoffs and maintaining efficiency. Hence, the design and planning of transportation system are strongly considered to be the most critical problems in transportation research.

Transportation system planning and design is a sequential procedure which generally contains two levels: strategic and operational. This dissertation conducts extensive research covering both levels, on the strategic planning level, two network design problems are studied and on the operational level, routing and scheduling problems are analyzed. The main objective of this study is utilizing operations research techniques to generate and provide managerial decision supports in designing reliable and efficient transportation system. Specifically, three practical problems in transportation system design and operations are explored. First, we collaborate with a public transit company to study the bus scheduling problem for a bus fleet with multiples types of vehicles. By considering different cost characteristics, we develop integer program and exact algorithm to efficiently solve the problem. Next, we examine the network design problem in emergency medical service and develop a novel two stage robust optimization framework to deal with uncertainty, then propose an approximate algorithm which is fast and efficient in solving practical instance. Finally, we investigate the major drawback of vehicle sharing program network design problem in previous research and provide a counterintuitive finding that could result in unrealistic solution. A new pessimistic model as well as a customized computational scheme are then introduced. We benchmark the performance of new model with existing model on several prototypical network structures. The results show that our proposed models and solution methods offer powerful decision support tools for decision makers to design, build and maintain efficient and reliable transportation systems.

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