| 引用本文: | 付亚平,黄敏,王洪峰,王兴伟.混合并行机调度问题的多目标优化模型及算法[J].控制理论与应用,2014,31(11):1510~1516.[点击复制] |
| FU Ya-ping,HUANG Min,WANG Hong-feng,WANG Xing-wei.Multi-objective optimization model and algorithm for hybrid parallel machine scheduling problem[J].Control Theory and Technology,2014,31(11):1510~1516.[点击复制] |
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| 混合并行机调度问题的多目标优化模型及算法 |
| Multi-objective optimization model and algorithm for hybrid parallel machine scheduling problem |
| 摘要点击 2974 全文点击 1453 投稿时间：2013-11-24 修订日期：2014-08-03 |
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| DOI编号 10.7641/CTA.2014.31233 |
| 2014,31(11):1510-1516 |
| 中文关键词 混合并行机调度问题 多目标优化 非支配排序遗传算法 局部搜索 |
| 英文关键词 hybrid parallel machine scheduling problem multiobjective optimization NSGA–II local search |
| 基金项目 国家杰出青年科学基金资助项目(71325002, 61225012); 国家自然科学基金资助项目(71071028, 71001018); 高等学校博士学科点专项科研基金优先发展领域资助课题(20120042130003); 高等学校博士学科点专项科研基金资助课题(20110042110024); 中央高校基本科研业务费专项资金资助项目(N110204003, N120104001, N130404017, N110204005); 流程工业综合自动化国家重点实验室基础科研业务费资助项目(2013ZCX11). |
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| 中文摘要 |
| 针对生产工序的合并造成一种串并联共存的生产布局, 研究了一种特殊的混合并行机调度问题, 并考虑以最小化总流水时间和最小化总延迟工件数量为目标的多目标调度问题, 建立了混合整数规划模型. 针对模型特点, 设计了一种改进的非支配排序遗传算法进行求解, 采用基于启发式方法的初始种群生成方式以提高种群的质量和多样性, 并引入一种局域搜索策略以改善求解算法所获得的非支配解的质量及分布性. 通过对大量数值算例进行仿真实验, 并与典型的多目标优化算法进行比较, 结果表明所提出的模型和算法在收敛性、分布性及极端点质量方面均具有优势, 能够较好的解决多目标混合并行机调度问题. |
| 英文摘要 |
| A special hybrid machine scheduling problem is investigated since the combination of production processes can yield a special layout with the coexistence of serial and parallel production. In order to address this problem effectively, a mixed integer programming multiobjective model, which aims to minimize both the total flow time and the total number of tardy jobs, is built and an improved nondominated sorting genetic algorithm II (NSGA–II), where a heuristic method is proposed to generate and improve the quality and diversity of initial population, and a local search strategy is embedded to improve the quality and distribution of the achieved nondominated solutions, is designed in this paper. Compared with the classical multiobjective optimization algorithms, the experimental results on a number of stochastic examples with different scale show that the proposed model and algorithm have advantage in the convergence, spread and extreme value point, and can address effectively the investigated hybrid parallel machine scheduling problem. |
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