论文:2016,Vol:34,Issue(4):635-641
引用本文:
李兢尧, 黄媛, 王军强, 郭阳明. 求解扩展双资源约束作业车间调度的分支种群遗传算法[J]. 西北工业大学学报
Li Jingyao, Huang Yuan, Wang Junqiang, Guo Yangming. Branch Population Genetic Algorithm for Extension Dual Resource Constrained Job Shop Scheduling Problem[J]. Northwestern polytechnical university

求解扩展双资源约束作业车间调度的分支种群遗传算法
李兢尧1, 黄媛2, 王军强3, 郭阳明4
1. 西北工业大学 第365研究所, 陕西 西安 710065;
2. 西北工业大学 机电学院, 陕西 西安 710072;
3. 西北工业大学 系统集成与工程管理研究所, 陕西 西安 710072;
4. 西北工业大学 计算机学院, 陕西 西安 710072
摘要:
根据扩展双资源约束作业车间调度问题的特点,构造了一种混合遗传算法进行求解:以分支种群为载体继承遗传进化经验,利用精英进化算子、基于扇形分割的轮盘赌选择算子及邻域搜索等机制,进一步优化了算法性能。通过分析策略对比仿真、算法性能对比仿真等实验,结果表明上述各种优化机制可行,且对于算法运算效率与寻优性能的优化效果均有良好表现。
关键词:    调度算法    扩展双资源约束    作业车间调度    分支种群    精英进化    扇形分割    邻域搜索   
Branch Population Genetic Algorithm for Extension Dual Resource Constrained Job Shop Scheduling Problem
Li Jingyao1, Huang Yuan2, Wang Junqiang3, Guo Yangming4
1. Research Institute of 365,Northwestern Polytechnical University, Xi'an 710065, China;
2. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
3. Institute of System Integrated and Engineering Management, Northwestern Polytechnical University, Xi'an 710072, China;
4. School of Computer, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
In this paper, a hybrid genetic algorithm was proposed for solving extension dual resource constrained job shop scheduling problem. The algorithm was constructed based on inheriting evolution experience of parent population with the branch population. In addition, this algorithm used some optimization operators to optimize algorithm performance, such as the elite evolutionary operator, the roulette selection operator based on sector partition, the variable neighbourhood search operator, and so on. Finally, the optimization performances of above mechanisms were validated according to the statistical analysis on the simulation results of strategies comparison simulation and algorithm performance comparison simulation.
Key words:    scheduling algorithm    extension dual resource constrained    job shop scheduling    branch population    elite evolutionary    sector partition    neighborhood search   
收稿日期: 2015-10-12     修回日期:
DOI:
基金项目: 国家自然科学基金(51275421)和西北工业大学基础研究基金(JC20120227)资助
通讯作者:     Email:
作者简介: 李兢尧(1984-),西北工业大学讲师,主要从事智能算法及调度优化研究。
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