[1]吴秀丽,张志强.求解柔性作业车间调度问题的细菌算法对比及改进[J].郑州大学学报(工学版),2018,39(03):34-39.
 The Comparison and Improvement of Bacterial Algorithms for Flexible Job Scheduling Problem[J].Journal of Zhengzhou University (Engineering Science),2018,39(03):34-39.
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求解柔性作业车间调度问题的细菌算法对比及改进()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
39
期数:
2018年03期
页码:
34-39
栏目:
出版日期:
2018-05-10

文章信息/Info

Title:
The Comparison and Improvement of Bacterial Algorithms for Flexible Job Scheduling Problem
作者:
吴秀丽张志强
文献标志码:
A
摘要:
为充分探讨该系列算法求解离散问题的能力,针对柔性作业车间调度问题,采用细菌趋化算法、细菌群体趋化算法、细菌进化算法、细菌群游算法和细菌觅食优化算法进行求解。首先建立了以完成时间为目标的柔性作业车间调度问题模型,然后用5种细菌算法进行求解,数值试验结果表明细菌觅食算法的寻优能力最强。接着,进一步对最细菌觅食算法进行了改进,针对其关键操作设计了数十种优化算子,最终得到优化能力最强的算法结构和优化算子组合。最后的数值实验表明,改进的细菌觅食算法在寻优能力及稳定性大幅提升,体现出非常好的全局开发能力和局部搜索能力。
Abstract:
The article aimed to fully explore the ability of bacterial algorithin and its varieties for solving the discrete optimization problems.The bacterial chemotaxis algorithm(BC), bacterial colony chemotaxis algorithm, bacterial evolutionary algorithm(BEA), bacterial swarming algorithm(BSA) and bacterial foraging optimization algorithm(BFO) are designed to solve the flexible job scheduling problem. Firstly, the model of the flexible job scheduling problem was formulated. Then the five algorithms were designed to solve the benchmark was instance. The results showed that the BFO outperformed the others Furthermove,a strategy to improve the BFO was proposed. More than ten optimization operators were designed and compared. Finally, the best structure of the improved BFO was built. The numerical experiments showed that the proposed BFO balanced the exploration and the exploitation very well and could solve FJSP effectively.
更新日期/Last Update: 2018-05-03