Advisor(s)

Emanuel Melachrinoudis (1946-)

Date of Award

2008

Date Accepted

12-19-2008

Degree Grantor

Northeastern University

Degree Level

M.S.

Degree Name

Master of Science

Department or Academic Unit

College of Engineering. Department of Mechanical and Industrial Engineering.

Keywords

Driver scheduling, Vehicle routing problem, Transportation

Subject Categories

Trucking, Operations research

Disciplines

Operational Research

Abstract

Driver fatigue is the cause of many truck crashes taking place today. In order to improve safety, the Federal Motor Carrier Safety Administration (FMCSA) has implemented revised Hours-of-Service (HOS) regulations effective on October 1^st 2005. According to the revised rules, drivers should take a break of 10 consecutive hours after 11 hours of driving time or 14 hours of duty time that includes driving time and service time such as loading and unloading cargo. This has caused a severe increase in the cost for the trucking industry which in turn hurt shippers and ultimately customers. A systematic way for routing vehicles to avoid traffic congestion and waiting due to truck arrival outside the customer service windows, as well as coordinating the timing drivers are taking their mandatory breaks, can improve the efficiency and safety of supply chain distribution operations. In this Thesis, a single truck routing and driver scheduling model with time-dependent travel times, HOS regulations, multiple delivery locations and service time windows is formulated and solved. The objective is to minimize the total time required to serve a given number of customers. The components of the total time are travel time, driver's break time, and waiting time and service time at the customer locations. For each segment of the transportation network, traffic congestion is modeled by using speed distribution profiles over the course of a day, which in turn makes the time required to traverse a highway segment dependent on the time the truck started traversing it. For a given set of customer locations, the optimization model determines the order in which they should be visited and the route between the consecutive customer locations in order to minimize the time of the tour subject to service time windows, HOS restrictions and time-dependent highway traversal times. A Simulated Annealing metaheuristic is implemented to obtain near optimal solutions of the problem. Our experimental results show that the heuristic provides good quality solutions for large size problems (with an average deviation of less than 1% from the optimal) in reasonable computation time. The accuracy comparison was obtained by solving smaller size problems consisting ofAnnouncement of 10 customers by explicit enumeration. The mathematical model and the solution approach can be easily adapted to more complex problems involving multiple capacitated vehicles with pickup and delivery.

Document Type

Master's Thesis

Rights Holder

Vidit Divyang Shah


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