求解柔性作业车间调度问题的细菌算法对比及改进  

The Comparison and Improvement of Bacterial Algorithms for Flexible Job Scheduling Problem

作　　者：吴秀丽[1] 张志强[1] WU Xiuli;ZHANG Zhiqiang(School of Mechanic Engineering,University of Science and Technology Beijing,Beijing 100083,China)

机构地区：[1]北京科技大学机械工程学院,北京100083

出　　处：《郑州大学学报（工学版）》2018年第3期34-39,共6页Journal of Zhengzhou University（Engineering Science）

基　　金：国家自然科学基金青年科学项目(51305024;71301054)

摘　　要：为充分探讨细菌系列算法求解离散优化问题的能力,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,进一步对细菌觅食算法进行了改进,针对其关键操作设计了数十种算子,最终得到优化能力最强的算法结构和算子组合.最后的数值实验表明,改进的细菌觅食算法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.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（ BCC）,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 instances. 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.

关 键 词：柔性作业车间调度 细菌趋化算法 细菌群体趋药性算法 细菌觅食算法 细菌群游算法 细菌进化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]