Electronic Theses and Dissertations

Identifier

2645

Alireza Naimi

Date

2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Engineering

Concentration

Civil Engineering

Committee Chair

Mihalis M. Golias

Committee Member

Sabyasachee Mishra

Committee Member

V. Charles Camp

Committee Member

Kyriacos Mouskos

Abstract

In today’s congested transportation networks, disruptions like crashes may cause unexpected and significant delays. All transportation networks are vulnerable to disruptions, to some extent, with temporary or permanent effects. Vulnerability is more important in urban transportation networks, due to heavy use and road segments that are close to each other. Small disturbances on an urban transportation network segment can have a huge impact on its accessibility. Intelligent adversaries may take advantage of these vulnerable parts of the network and disrupt transportation operations, increasing the overall transportation cost for the users.Often, the decision about improving the networks in transportation planning and management is made without adequately considering the possible vulnerabilities. By considering the factor of vulnerability in their decision, planners could prevent or limit the impact of severe unforeseen disruptions. This dissertation proposes two models for designing robust networks against intelligent attackers. In both models, three stakeholders are considered: i) the network manager/designer, ii) the adversary (intelligent attacker), and iii) the network users. The frameworks of both models and some other possible models are presented in this dissertation.The first framework is a bi-objective designer model. The designer in this model has two objectives at the top level: to reduce the total system cost and to reduce the vulnerability of the network. The Sioux Falls network consists of 24 nodes and 76 links was chosen for to evaluate this framework. The decision of the designer and attacker was improving or destroying the links. Metaheuristic algorithm was used to solve the designer and attacker problems. For the user equilibrium problem, the Frank-Wolfe algorithm was implemented. The objective of the designer of the network in the first model, consist of two goals. The two goals may conflict on the amount of amount of limited available budget to be invested on the desired project/links. Therefore, a trade off solutions between these two objectives may forms. The results proved that the proposed multi-level model is able to find the Pareto front solutions for the two objectives of the designer. The second framework is a three-level zero-sum game model. In this framework, the payoffs from the designer are assumed to have the same value to the adversary entity. Therefore, the goal of this framework is to minimize the maximum gain that the adversary can achieve. An example network with 6 nodes and 16 links was used to examine this framework. The results showed that the model could be a valuable tool to reduce the potential vulnerability of networks. Other indicators of system performance can be implemented in the upper-level of this framework, in order to examine different goals. Both frameworks were tested using a medium size network with applications to larger scale networks as a future research direction.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.

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