DocumentCode :
507843
Title :
Vehicle Routing Problem with Time Windows: A Hybrid Particle Swarm Optimization Approach
Author :
Liu, Xiaoxiang ; Jiang, Weigang ; Xie, Jianwen
Author_Institution :
Dept. of Comput. Sci., Jinan Univ., Zhuhai, China
Volume :
4
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
502
Lastpage :
506
Abstract :
Vehicle routing problem (VRP) is a well-known combinatorial optimization and nonlinear programming problem seeking to service a number of customers with a fleet of vehicles. This paper proposes a hybrid particle swarm optimization (HPSO) algorithm for VRP. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to make its manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the HPSO algorithm to an example of VRP, and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of HPSO algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.
Keywords :
genetic algorithms; nonlinear programming; particle swarm optimisation; set theory; transportation; algorithm convergence speed; combinatorial optimization; genetic algorithm; hybrid particle swarm optimization approach; level set theory; nonlinear programming problem; time windows; vehicle routing problem; Computer science; Convergence; Educational institutions; Genetic algorithms; Level set; Mathematical model; Particle swarm optimization; Quality of service; Routing; Vehicles; Particle Swarm Optimization; Vehicle Routing Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.353
Filename :
5363419
Link To Document :
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