变邻域改进遗传算法求解混合流水车间调度问题

发布时间：2018-02-22 10:34

本文关键词： 混合流水车间调度改进遗传算法变邻域搜索 NEH启发式算法　出处：《计算机集成制造系统》2017年09期 　论文类型：期刊论文

【摘要】：针对混合流水车间调度问题的NP难特性,提出一种改进的混合变邻域搜索的遗传算法。建立了数学模型,提出了算法的总体流程,设计了基于操作的编码和解码方法,并采用NEH启发式算法产生初始种群。随机采用基于位置的交叉和线性次序交叉,选用反转逆序的变异算子,交叉变异后合并子代与父代,保留较优个体,对当前最优个体执行变邻域搜索,以增强遗传算法的局部搜索能力。通过初始对比实验,证明了NEH启发式算法能够产生质量更好的初始解,随机采取两种交叉算子能够提高算法的搜索效率,标准算例实验结果表明所提算法能够有效求解混合流水车间调度问题。
[Abstract]:In view of the NP-hard characteristics of hybrid income job-shop scheduling problem, an improved hybrid variable neighborhood search genetic algorithm is proposed. The mathematical model is established, the overall flow of the algorithm is proposed, and the operation-based coding and decoding methods are designed. The initial population is generated by NEH heuristic algorithm. The crossover and linear order crossover based on position are used randomly, and the mutation operator of reverse order is selected. After crossover and mutation, the offspring and the parent generation are merged, and the better individuals are retained. In order to enhance the local search ability of genetic algorithm (GA), the variable neighborhood search is performed on the current optimal individuals. Through the initial contrast experiment, it is proved that the NEH heuristic algorithm can produce a better quality initial solution. Using two crossover operators at random can improve the search efficiency of the algorithm. The experimental results of standard examples show that the proposed algorithm can effectively solve the hybrid income job shop scheduling problem.
【作者单位】：北京科技大学机械工程学院;华南理工大学工商管理学院;
【基金】：国家自然科学基金资助项目(51305024,71301054)~~
【分类号】：TB497;TP18

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