Particle Swarm Optimization for Open Vehicle Routing Problem
The Open Vehicle Routing Problem was brought forward several decades ago, but it has still received little attention from researchers for a satisfactory solution. In this paper, a novel real number encoding method of Particle Swarm Optimization (PSO) for Open Vehicle Routing Problem is proposed. The vehicle is mapped into the integer part of the real number; and the sequence of customers in the vehicle is mapped into the decimal fraction of the real number. After decoding, several heurist methods are applied into the post-optimization procedure, such as Nearest Insertion algorithm, GENI algorithm, and 2-Opt. They are used to optimize the inner or outer routes and modify illegal solutions. In the experiments, a number of numerical examples are carried out for testing and verification. The performance of the proposed post-optimization algorithm is analyzed and the particle swarm optimization algorithm is compared with other heuristic methods for the same problem.
KeywordsParticle Swarm Optimization Particle Swarm Optimization Algorithm Travel Salesman Problem Travel Salesman Problem Vehicle Route Problem
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