Particle Swarm Optimization for Vehicle Routing Problem with Time Windows
The investigation of the performance of the Particle Swarm Optimization (PSO) method for Vehicle Routing Problem with Time Windows is the main theme of the paper. “Exchange minus operator” is constructed to compute particle’s velocity. We use Saving algorithm, Nearest Neighbor algorithm, and Solomon insertion heuristics for parameter initialization and apply the “Routing first and Cluster second” strategy for solution generation. By PSO, customers are sorted in an ordered sequence for vehicle assignment and Nearest Neighbor algorithm is used to optimize every vehicle route. In our experiments, two different PSO algorithms (global and local), and three construct algorithms are investigated for omparison. Computational results show that global PSO algorithm with Solomon insertion heuristics is more efficiency than the others.
Xing Ai, Jianfeng Li and Chuanzhen Huang
Y. W. Zhao et al., "Particle Swarm Optimization for Vehicle Routing Problem with Time Windows", Materials Science Forum, Vols. 471-472, pp. 801-805, 2004