Evaluation of vehicle routing problem with time windows by using metaheuristics algorithm

Authors:
A. M. Nasir;S. Masrom;N. Ahmad
Affiliations:
Malaysia Institute of Transport, Faculty of Computer and Mathematical Science, Universiti Teknologi MARA, Perak, Malaysia;Malaysia Institute of Transport, Faculty of Computer and Mathematical Science, Universiti Teknologi MARA, Perak, Malaysia;Faculty of Computing and Mathematical Science, Universiti Teknologi MARA, Malaysia
Venue:
ACC'11/MMACTEE'11 Proceedings of the 13th IASME/WSEAS international conference on Mathematical Methods and Computational Techniques in Electrical Engineering conference on Applied Computing
Year:
2011

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Abstract

Vehicle routing problem with Time Window (VRPTW) has received much attention by researchers in solving many scheduling applications for transportation and logistics. The objective of VRPTW is to use a fleet of vehicles with specific capacity to serve a number of customers with various demands and time window constraints. As a non-polynomial (NP) hard problem, the VRPTW is complex and time consuming, especially when it involves a large number of customers and constraints. This paper presents a metaheuristics approach for solving VRPTW. The Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been selected as the two metaheuristics algorithm. A computational experiment has been carried out by running the PSO and GA with the VRPTW benchmark data set. The empirical results show that PSO perform better than GA when tested on clustered based customer distribution. On the other hand, GA is superior to PSO on the random customer distributions. In term of computing time, the performance of PSO algorithm is better than GA.