机构地区: 华南理工大学工商管理学院
出 处: 《计算机应用研究》 2011年第9期3324-3326,共3页
摘 要: 针对细菌觅食算法(BFOA)求解高维优化问题时容易陷入局部最优和早熟的问题,引入自适应步长及差分进化算子,并将改进算法用于车间作业调度问题(JSP)中。求解时,设计了一种编码转换方案,从而无须修改BFOA运算规则即可实现对JSP的寻优;同时,采用空闲时间片段优化策略降低了调度问题的复杂性。仿真实验表明,该算法能够跳出局部最优,避免了早熟的问题,调度结果优于原始细菌觅食算法和离散粒子群算法。 This paper designed an improved adaptive chemotactic step and differential evolution for solving local-optimal and premature problems in the large multi-dimension optimization problem,and applied this new algorithm to optimizing JSP.When dealing with JSP,adopted a code conversion to optimize JSP without changing the BFOA rule;and also introduced free time optimization strategy to reduce complexity of problems.Numerical simulation shows that the new algorithm has avoided local-optimal and premature problems,and is superior to standard BFOA and discrete PSO algorithm.
关 键 词: 细菌觅食算法 自适应步长 车间作业调度问题 编码转换 空闲时间片段优化
领 域: [自动化与计算机技术] [自动化与计算机技术]