Title :
Particle Swarm Optimization Based on the Average Optimal Information for Vehicle Routing Problem
Author :
Zhuangkuo Li ; Yannan Ma
Author_Institution :
Sch. of Bus., Guilin Univ. of Electron. Technol., Guilin, China
Abstract :
According to the weakness of standard particle swarm optimization in dealing with vehicle routing problem (VRP), based on the definition of particle swarm optimization, this paper introduce the average information of individual and the global information to the standard PSO. A new hybrid form of PSO (AVGPSO), which is based on the mean information of individual optimal information and the global optimal information, is brought forward. This proposed algorithm is applied to VRP and compared with standard particle swarm optimization. The result shows that the proposed algorithm has better probability for solving VRP.
Keywords :
particle swarm optimisation; probability; vehicle routing; AVGPSO; VRP; average optimal information; global optimal information; individual average information; individual optimal information; probability; standard particle swarm optimization; vehicle routing problem; Encoding; Optimization; Particle swarm optimization; Routing; Standards; Vectors; Vehicles; average optimal information; combination optimization; particle swarm optimization; vehicle routing problem;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
DOI :
10.1109/ISCID.2013.20