A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2004.11.019 Byline: K.C. Tan (a), Y.H. Chew (a), L.H. Lee (b) Keywords: Vehicle routing; Evolutionary algorithms; Multi-objective optimization Abstract: This paper considers a transportation problem for moving empty or laden containers for a logistic company. Owing to the limited resource of its vehicles (trucks and trailers), the company often needs to sub-contract certain job orders to outsourced companies. A model for this truck and trailer vehicle routing problem (TTVRP) is first constructed in the paper. The solution to the TTVRP consists of finding a complete routing schedule for serving the jobs with minimum routing distance and number of trucks, subject to a number of constraints such as time windows and availability of trailers. To solve such a multi-objective and multi-modal combinatorial optimization problem, a hybrid multi-objective evolutionary algorithm (HMOEA) featured with specialized genetic operators, variable-length representation and local search heuristic is applied to find the Pareto optimal routing solutions for the TTVRP. Detailed analysis is performed to extract useful decision-making information from the multi-objective optimization results as well as to examine the correlations among different variables, such as the number of trucks and trailers, the trailer exchange points, and the utilization of trucks in the routing solutions. It has been shown that the HMOEA is effective in solving multi-objective combinatorial optimization problems, such as finding useful trade-off solutions for the TTVRP routing problem. Author Affiliation: (a) Department of Electrical and Computer Engineering, National University of Singapore, 4, Engineering Drive 3, Singapore 117576, Singapore (b) Department of Industrial and System Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore Article History: Received 18 March 2004; Accepted 9 November 2004