| 基于自适应遗传算法的Job Shop调度问题研究 |
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| 引用本文： | 沈斌,周莹君,王家海.基于自适应遗传算法的Job Shop调度问题研究[J].计算机应用,2009,29(Z2). |
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| 作者姓名： | 沈斌 周莹君 王家海 |
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| 作者单位： | 1. 同济大学,中德学院,上海,200092
2. 同济大学,机械工程学院,上海,200092 |
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| 摘 要： | 求解Job Shop调度问题是个NP完全问题,为了提高遗传算法的性能,提出一种新的自适应遗传算法(NSGA)以解决Job Shop调度问题.采用活动调度解码方法、过滤个体适应度相同的筛选策略、改进自适应交叉变异概率等改进策略来提高算法性能,最后通过仿真比较分析证明该算法的先进性.
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| 关 键 词： | 自适应遗传算法 作业车间调度 算法改进 |
Research of Job Shop scheduling problem based on self-adaptive genetic algorithm |
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| SHEN Bin,ZHOU Ying-jun,WANG Jia-hai.Research of Job Shop scheduling problem based on self-adaptive genetic algorithm[J].journal of Computer Applications,2009,29(Z2). |
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| Authors: | SHEN Bin ZHOU Ying-jun WANG Jia-hai |
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| Abstract: | It is well known that Job Shop scheduling problem is a Non-Polynomial (NP) complete problem. For improving the performance of Genetic Algorithm (GA), a new self-adaptive genetic algorithm (NSGA) was proposed to solve Job Shop scheduling problem. The improved methods included decoding the active scheduling, filtering the individual of the same fitness value, and improving self adaptive probability. Finally, the NSGA was tested on 8 famous Car benchmarks. The simulation results show that the improved algorithm is more effective with comparison of the normal genetic algorithm. |
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| Keywords: | adaptive Genetic Algorithm (GA) Job Shop scheduling improvement algorithm |
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