基于改进ICA算法的LBFFSP问题研究
发布时间：2018-12-16 04:42
【摘要】：为了解决带有限缓冲区的柔性流水车间排产优化问题(Limited-Buffer Flexible Flow-shop Scheduling Problem,LBFFSP),首先建立LBFFSP的数学模型,提出了一种改进帝国竞争算法(improved imperialist competitive algorithm,IICA)作为全局优化算法,在标准帝国竞争算法基础上,引入模拟退火思想,扩大算法搜索范围,并加入离散化处理操作、改革操作、以及精英个体保留策略三处改进.为进一步提高算法搜索最优解效率,设计了一种基于优化目标的初始种群建立方法,并加入基于汉明距离的个体选择机制,以提高初始种群中初始解的质量.设计仿真实验,对算法中的参数进行分析探讨,确定最佳参数值.最后通过实例测试,将IICA算法与其他算法进行对比研究,验证了IICA算法对于解决柔性流水车间有限缓冲区的排产优化问题的有效性.
[Abstract]:In order to solve the problem of flexible flow shop scheduling optimization (Limited-Buffer Flexible Flow-shop Scheduling Problem,LBFFSP) with finite buffer zone, the mathematical model of LBFFSP is first established, and an improved imperial competition algorithm (improved imperialist competitive algorithm, is proposed. IICA) as a global optimization algorithm, based on the standard imperial competition algorithm, the simulated annealing algorithm is introduced, the search scope of the algorithm is expanded, and three improvements are introduced, such as discretization operation, reform operation, and elite individual retention strategy. In order to improve the efficiency of searching the optimal solution, a method of establishing the initial population based on the optimization objective is designed, and an individual selection mechanism based on hamming distance is added to improve the quality of the initial solution in the initial population. Design the simulation experiment, analyze the parameters in the algorithm, and determine the best parameter value. Finally, the IICA algorithm is compared with other algorithms through an example test, which verifies the effectiveness of the IICA algorithm in solving the scheduling optimization problem of flexible workshop limited buffer.
【作者单位】： 沈阳建筑大学信息与控制工程学院;中国科学院沈阳自动化研究所;
【基金】：国家自然科学基金资助项目(61503259) 辽宁省科技厅项目(201602608)
【分类号】：TH165;TP18
本文编号：2381827
[Abstract]:In order to solve the problem of flexible flow shop scheduling optimization (Limited-Buffer Flexible Flow-shop Scheduling Problem,LBFFSP) with finite buffer zone, the mathematical model of LBFFSP is first established, and an improved imperial competition algorithm (improved imperialist competitive algorithm, is proposed. IICA) as a global optimization algorithm, based on the standard imperial competition algorithm, the simulated annealing algorithm is introduced, the search scope of the algorithm is expanded, and three improvements are introduced, such as discretization operation, reform operation, and elite individual retention strategy. In order to improve the efficiency of searching the optimal solution, a method of establishing the initial population based on the optimization objective is designed, and an individual selection mechanism based on hamming distance is added to improve the quality of the initial solution in the initial population. Design the simulation experiment, analyze the parameters in the algorithm, and determine the best parameter value. Finally, the IICA algorithm is compared with other algorithms through an example test, which verifies the effectiveness of the IICA algorithm in solving the scheduling optimization problem of flexible workshop limited buffer.
【作者单位】： 沈阳建筑大学信息与控制工程学院;中国科学院沈阳自动化研究所;
【基金】：国家自然科学基金资助项目(61503259) 辽宁省科技厅项目(201602608)
【分类号】：TH165;TP18
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