A New Hybrid Particle Swarm Optimization for Solving Flow Shop Scheduling Problem with Fuzzy due Date

Abstract:

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Coping with the characteristic of flow shop scheduling problem with uncertain due date, fuzzy arithmetic on fuzzy numbers is applied to describe the problem, and then a new hybrid algorithm model which integrate particle swarm optimization into the evolutionary mechanism of the knowledge evolution algorithm is presented to solve the problem. By the evolutionary mechanism of knowledge evolution algorithm, we can exploit the global search ability. By the operating characteristic of PSO, we can enhance the local search ability. The algorithm is tested with MATLAB simulation. The result, compared with Genetic algorithm and modified particle swarm optimization, shows the feasibility and effectiveness of the proposed algorithm.

Info:

Periodical:

Advanced Materials Research (Volumes 189-193)

Edited by:

Zhengyi Jiang, Shanqing Li, Jianmin Zeng, Xiaoping Liao and Daoguo Yang

Pages:

2746-2753

DOI:

10.4028/www.scientific.net/AMR.189-193.2746

Citation:

H. B. Tang et al., "A New Hybrid Particle Swarm Optimization for Solving Flow Shop Scheduling Problem with Fuzzy due Date", Advanced Materials Research, Vols. 189-193, pp. 2746-2753, 2011

Online since:

February 2011

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Price:

$35.00

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