Vehicle routing for hazardous material transportation (2018)
The main objective of this thesis is to study the hazardous materials (HazMat) transportation problem considered as a heterogeneous fleet vehicle routing problem. HazMat transportation decisions comprise different and sometimes conflicting objectives. Two are considered in this work, the total routing cost and the total routing risk. The first task undertaken was the formulation of a mathematical model for the routing risk minimization, which depends on the type of vehicle, the material being transported, and the load change when the vehicle goes from one customer to another. A piecewise linear approximation is employed to keep a mixed integer linear programing formulation. Hybrid solution methods based on neighborhood search are explored for solving the routing risk minimization. This includes the study of neighborhood structures and the development of a Variable Neighborhood Descent (VND) algorithm for local search, and a perturbation mechanism (shaking neighborhoods). A postoptimization procedure is applied to improve the solution quality. Finally, two different solution approaches, a multi-objective dominance-based algorithm and a meta-heuristic ϵ-constraint method are employed for addressing the multi-objective version of the problem. Two performance metrics are used: the hypervolume and the ∆-metric. The front approximations show that a small increment in the total routing cost can produce a high reduction in percentage of the expected consequences given the probability of a HazMat transportation incident.