Cloud Particle Swarm Optimization for Vehicle Routing Problem

Bin Tian; Yan Yan Wang

doi:10.4028/www.scientific.net/AMM.333-335.1397

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Training Back-Propagation Neural Network for Target Localization Using Improved Particle Swarm Optimization
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A Combined Local Best Particle Swarm Optimization Algorithm
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Cloud Particle Swarm Optimization for Vehicle Routing Problem
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Iterative Methods for Strictly Pseudo-Contractive Mappings
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335Cloud Particle Swarm Optimization for Vehicle...

Cloud Particle Swarm Optimization for Vehicle Routing Problem

Abstract:

Vehicle routing problem (VRP) is a kind of NP combination problem. In order to overcome PSOs premature convergence, a Cloud Particle Swarm Optimization (CPSO) is put forward, it uses the randomicity and stable tendentiousness characteristics of cloud model, adopts different inertia weight generating methods in different groups, the searching ability of the algorithm in local and overall situation is balanced effectively. In the paper, the algorithm is used to solve VRP, a kind of new particles coding method is established and the solution algorithm is developed. The simulation results prove that the algorithm has more search speed and stronger optimization ability than GA and the PSO algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

1397-1401

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.1397

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Online since:

July 2013

Authors:

Bin Tian*, Yan Yan Wang

Keywords:

Cloud Model, Particle Swarm Optimization (PSO), Vehicle Routing Problem (VRP)

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