Study on optimization of hazardous material transportation via lane reservation

Overview & Synopsis

Hazardous material transportation is well-known for its high potential risk. An accident may cause very serious economic damage and negative impacts on the public health and the environment over the long term. Optimization for hazardous material transportation is an important issue. For the first time in the literature, this thesis introduces the lane reservation strategy into the hazardous material transportation problem. The goal is to obtain a best compromise between the impact on normal traffic due to lane reservation and the transportation risk.In this thesis, we focus on two novel problems: hazardous material transportation problem via lane reservation in networks with time-invariant and time-dependent risk, called LRPTIR and LRPTDR, respectively. For these problems, multi-objective integer programming and multi-objective mixed integer programming models are formulated, respectively. For the LRPTIR, we first develop an ε-constraint and fuzzy-logic based method to obtain Pareto optimal solutions and a preferred solution. Then a cut-and-solve and cutting plane combined method is proposed to reduce the computational time. For the LRPTDR, an improved cut-and-solve based ε-constraint method is proposed, in which a new technique of generating piercing cuts is developed and a partial integral relaxation strategy is applied. The performance of the proposed algorithms is evaluated by randomly generated instances. Computational results demonstrate that for the considered problems, the cut-and-solve method outperforms software package CPLEX.