Optimization Mechanism Control Strategy of Vehicle Routing Problem Based on Improved PSO

Jun Ting Zhang; Li Xia Qiao

doi:10.4028/www.scientific.net/AMR.681.130

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 681Optimization Mechanism Control Strategy of Vehicle...

Optimization Mechanism Control Strategy of Vehicle Routing Problem Based on Improved PSO

Abstract:

Traveling salesman problem based on vehicle routing problem in the case, according to the discrete domain specificity, redefine the problem domain to the mapping relationship between particles and related operation rules, and the introduction of self learning operator so that the PSO algorithm can deal with discrete problem. Vehicle Routing Problem (VRP) is research on how to plan the vehicles routes in order to save the transportation cost. Improved Particle Swarm Optimization (PSO) algorithm is proposed to solve the VRP in this paper. To improve the efficiency of the Particle Swarm Optimization, self-learning operator is constructed. Particles are re coded and operate rules are redefined to deal with the discrete problem of VRP. The effectiveness of the proposed algorithm is demonstrated by the simulations.

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Periodical:

Advanced Materials Research (Volume 681)

Pages:

130-136

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.681.130

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Online since:

April 2013

Authors:

Jun Ting Zhang, Li Xia Qiao

Keywords:

Improved PSO, Mechanism Control, Particle Swarm Optimization (PSO), Routing Problem

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