Based Stochastic Particle Swarm Optimization and Random Simulation for Solving Stochastic Dependent-Chance Programming

Ning Xiao

doi:10.4028/www.scientific.net/AMM.496-500.1960

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 496-500Based Stochastic Particle Swarm Optimization and...

Based Stochastic Particle Swarm Optimization and Random Simulation for Solving Stochastic Dependent-Chance Programming

Abstract:

Aiming at being hard to solve stochastic Dependent-chance Programming in uncertainty programming,a new algorithm for stochastic dependent-chance programming combined particle swarm optimization with random simulation for approximation of the chance function is presented in the paper.It overcomes the defaults such as needing a long time,complex calculation,easy falling into local optimal in the hybrid intelligence algorithm based on GA,the result of experiment shows the correctness and effectiveness of the algorithm.After testing its performance and comparing with algorithm of based on GA,the results show that the algorithm is more preferable.

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Periodical:

Applied Mechanics and Materials (Volumes 496-500)

Pages:

1960-1964

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.496-500.1960

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Online since:

January 2014

Authors:

Ning Xiao*

Keywords:

Random Simulation, SDCP, SPSO

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* - Corresponding Author

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