基于文化基因算法的集成工艺规划与调度研究

发布时间：2018-04-12 17:18

本文选题：工艺规划 + 车间调度　；参考：《华中科技大学学报(自然科学版)》2017年03期

【摘要】：建立了与工艺规划集成的调度问题的数学模型.以最大完工时间为目标,设计一种混合文化基因算法求解该问题.在提出算法中,设计了新型编码和主动解码方案,使用变邻域搜索(VNS)算法进行局部搜索,引入了高效的邻域结构以强化算法的局部搜索能力,并提出了一种个体扰动方法,以避免群体多样性趋于单一,使得提出算法在分散搜索和集中搜索之间达到更合理的平衡.为测试算法的性能,对现有的基准问题进行了测试,有21个实例达到了下界或得到改进,成为当前新的最优解.对比已有的最优结果可见:提出的算法可高效地求解工艺规划与车间调度集成问题且优于其他算法.
[Abstract]:The mathematical model of scheduling problem integrated with process planning is established.Aiming at the maximum completion time, a hybrid genetic algorithm is designed to solve the problem.In the proposed algorithm, a new coding and active decoding scheme is designed, and the variable neighborhood search (VNS) algorithm is used for local search. An efficient neighborhood structure is introduced to enhance the local search ability of the algorithm, and an individual perturbation method is proposed.In order to avoid a single population diversity, the proposed algorithm achieves a more reasonable balance between decentralized search and centralized search.In order to test the performance of the algorithm, the existing benchmark problem is tested. 21 examples have reached the lower bound or improved, and become the new optimal solution.Comparing with the existing optimal results, it can be seen that the proposed algorithm can efficiently solve the process planning and job shop scheduling integration problems and is superior to other algorithms.
【作者单位】：华中科技大学数字制造装备与技术国家重点实验室;
【基金】：国家自然科学基金资助项目(51575211);国家自然科学基金国际(地区)合作与交流项目(51561125002) 湖北省自然科学基金资助项目(2014CFB348) 中央高校基本科研业务费专项资金资助项目(2014TS038)
【分类号】：TB497

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