Research on Particle Swarm Genetic Algorithm for Scheduling of Discrete Manufacturing Industry
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    Abstract:

    In discrete manufacturing industry, the pros and cons of production scheduling method directly affects the efficiency of production. In order to make the algorithm be better applied to the production scheduling, characteristics of discrete manufacturing industry production are analyzed. At the same time, in order to improve the search performance of the algorithm, the advantages and disadvantages of genetic algorithm and particle swarm optimization algorithm are analyzed, and a PSO_GA hybrid algorithm is proposed. In this algorithm, introducing parameters on the basis of genetic algorithm, thus crossover and mutation are automatically controlled for each iteration. Then, population diversity is improved. In order to overcome the disadvantage of genetic algorithm with low convergence rate, particle swarm optimization algorithm is introduced in the appropriate iteration cycle, so as to improve the search speed and precision of the algorithm. Finally, the results of simulation experiments for production scheduling model verify the search performance of the algorithm.

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陈园园,夏筱筠,柏松,宋佳.粒子群遗传算法在离散制造业排产中的研究.计算机系统应用,2016,25(5):94-100

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History
  • Received:August 19,2015
  • Revised:October 09,2015
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  • Online: May 20,2016
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