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
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