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华东理工大学学报(自然科学版):2017,43(3):425-435
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基于离散布谷鸟搜索算法的带阻塞有差速混合流水车间调度
陈飞跃, 徐震浩, 顾幸生
(华东理工大学化工过程先进控制和优化技术教育部重点实验室, 上海 200237)
Discrete Cuckoo Search Algorithm for Blocking and Unrelated Hybrid Flow Shop Scheduling Problem
CHEN Fei-yue, XU Zhen-hao, GU Xing-sheng
(Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China)
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投稿时间:2016-09-28    
中文摘要: 基于以最小完工时间为目标的带阻塞有差速混合流水车间调度问题,提出了一种改进的离散布谷鸟搜索算法。在基本布谷鸟搜索算法的莱维飞行和巢寄生性的基础结构上,提出了一种基于交叉策略的莱维飞行机制,以便算法能够解决离散问题;同时,通过非余弦递减策略的动态发现概率去发现劣质鸟巢,并利用排列差分进化算法的变异思想将劣质鸟巢重建;在搜索过程中设定全局最优极值保持代数为阈值去重新发现劣质鸟巢,以防止算法陷入局部最优;最后利用邻域搜索方法进一步提高算法的搜索精度。通过仿真实验验证了该算法在求解混合流水车间调度类离散问题上的有效性与优越性。
Abstract:For the hybrid flow shop scheduling problem of minimizing the total flow time subject to blocking and differential speed,this paper proposes a discrete cuckoo search algorithm (DCS).By means of the Levy flight and the brood parasite of the cuckoo search algorithm,this paper proposes a crossover strategy based Levy flight mechanism so that the DCS can solve the discrete optimization problems.And then,the dynamic detection probability method is utilized to search for the inferior nest that is further reconstructed by adopting the mutation technique of the permutation-based differential evolution.In order to prevent the DCS from falling into local extremism,this paper introduces the global optimum extreme value algebra as the threshold to rediscover the inferior nests.Finally,the neighborhood search algorithm is used to further improve the search accuracy.The simulation results verify the effectiveness of the proposed algorithm for solving the hybrid flow shop scheduling problems subject to blocking.
文章编号:     中图分类号:TP301    文献标志码:
基金项目:国家自然科学基金(61104178,61174040)
引用本文:
陈飞跃,徐震浩,顾幸生.基于离散布谷鸟搜索算法的带阻塞有差速混合流水车间调度[J].华东理工大学学报(自然科学版),DOI:10.14135/j.cnki.1006-3080.2017.03.020.

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