运筹与管理 ›› 2018, Vol. 27 ›› Issue (3): 113-117.DOI: 10.12005/orms.2018.0066

• 理论分析与方法探讨 • 上一篇    下一篇

具有学习效应和加工时间可控的平行机排序问题

郭苗苗1, 刘桓2, 王吉波1,3, 牛玉萍1   

  1. 1.沈阳航空航天大学 经济与管理学院,辽宁 沈阳 110136;
    2.辽宁省体育学校 教务科,辽宁 沈阳 110179;
    3.沈阳航空航天大学 理学院,辽宁 沈阳 110136
  • 收稿日期:2016-08-31 出版日期:2018-03-25
  • 作者简介:郭苗苗,女,河北邢台人,硕士研究生,研究方向:企业运作管理;刘桓,女,辽宁沈阳人,硕士,研究方向:数学教育;王吉波,男,辽宁沈阳人,博士,教授,博导(兼职),主要从事生产计划与排序的研究;牛玉萍,女,山东烟台人,硕士生,研究方向:企业运作管理。
  • 基金资助:
    国家自然科学基金资助项目(71471120);辽宁省高等学校创新人才支持计划(LR201617)

Parallel Machines Scheduling with Learning Effect and Controllable Processing Times

GUO Miao-miao1, LIU Huan2, WANG Ji-bo1,3, NIU Yu-ping1   

  1. 1.School of Economics and Management, Shenyang Aerospace University, Shenyang 110136, China;
    2.Department of Educational Administration, Liaoning Sports School, Shenyang 110179, China;
    3.School of Science, Shenyang Aerospace University, Shenyang 110136, China
  • Received:2016-08-31 Online:2018-03-25

摘要: 本文研究了一类不相关平行机的排序问题,在该问题中工件的加工时间既具有学习效应,又资源可控,也就是说在该问题模型中,工件的实际加工时间为其正常的加工时间、加工过程中工件所处位置以及加工时间可控这些变量的函数。该研究的目的是为使得总机器负载和总的控制费用的加权和最小以及总的完工时间和总的控制费用的加权和最小。文章通过对问题的相关性质的分析和证明找到了一个解决问题的最优化算法,并且也证明了在处理机的数量给定的条件下,该问题的时间复杂性为O(nm+2),最后也给出了相应的数值例子来阐述该问题。

关键词: 排序, 平行机, 学习效应, 加工时间可控

Abstract: In this paper we consider the unrelated parallel machines scheduling problem, in the problem the job of the processing time is with learning effect and necource controllable, that is to say in the model of this problem the job’s actual processing time is the function of the basic processing time, the location of the job (learning effect) and the controllable of the processing time. The objective function is to minimize the weighted sum of total machine load and total control cost, and minimize the weighted sum of total completion time and total control cost. The article found an optimization algorithm to solve the problem through the analysis of the related nature of the problem, and also proved that in the number of processor is a given condition, the time complexity of the problem is O(nm+2). Finally the paper also gives corresponding numerical example to illustrate this problem.

Key words: scheduling, parallel machine, learning effect, controllable job processing times

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