Date of Completion

5-14-2020

Embargo Period

5-13-2022

Keywords

Transportation; Trucking; Analytics; Optimization;

Major Advisor

David Bergman

Co-Major Advisor

Robert Day

Associate Advisor

Sudip Bhattacharjee

Associate Advisor

Nicholas Lownes

Field of Study

Business Administration

Degree

Doctor of Philosophy

Open Access

Campus Access

Abstract

This dissertation focuses on designing decision support systems for efficient management in trucking transportation. The first essay introduces a new variant of simultaneous pickup and delivery problems in which arrival-time consistency is considered. This problem is motivated by the real operations of an instrument-calibration company in a Scandinavian country. This is a challenging optimization problem, and we present frameworks for identifying optimal solutions for the company to reduce transportation costs while enforcing a variety of practical considerations.

In the second essay, we apply spatial analytics on GPS and other sensor data from trucks to identify potential backhaul opportunities for a company that has a significant number of empty truck hauls. We use data-mining techniques on real data collected from multiple carriers in the US to identify frequent transportation lanes. The identified lanes are then used as inputs to an optimization problem to determine financial, environmental, and social benefits. The underlying optimization problem is challenging, and we introduce an efficient solution procedure to solve the resulting carrier collaboration problem.

In the third essay, we design an electronic transportation market to solve the carrier collaboration problem, proposing efficient exchange mechanisms among carriers. This combinatorial procurement auction problem has been studied in the literature; however, many of the extant proposed mechanisms ignore important practical challenges for the carriers participating in the auction, and do not analyze the economics of the problem to the extent covered here. In this research, we highlight the advantages of using a compact-bid language for the participating carriers in the auction, i.e., helping carriers to express their preferences using polynomially sized parameters, and to solve the combinatorial winner determination problem optimally. We, then, develop a dual-pricing mechanism that incorporates the compact-bid language into payment calculations and find prices that satisfy budget balance, individual rationality, and competitive equilibrium.

Available for download on Friday, May 13, 2022

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