| 具有学习和退化效应的单机干扰管理问题 |
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| 引用本文： | 刘春来,王建军.具有学习和退化效应的单机干扰管理问题[J].运筹与管理,2019,28(1):94-100. |
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| 作者姓名： | 刘春来 王建军 |
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| 作者单位： | 1.杭州电子科技大学 管理学院,浙江 杭州 310018; 2.大连理工大学 管理与经济学部,辽宁 大连 116023 |
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| 基金项目： | 国家自然科学基金资助项目(71672019,71271039,71421001);浙江省自然科学基金资助项目(LQ19G020010) |
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| 摘 要： | 针对工件同时具有学习和退化效应、机器具有可用性限制这一问题,建立可预见性单机干扰管理模型。在这一模型中,工件的加工时间是既与工件所排的加工位置又与工件开始加工的时间有关的函数。同时,在生产过程中由于机器发生故障或定期维修等扰动事件导致机器在某段时间内不能加工工件。目标是在同时考虑原目标函数和由扰动造成的偏离函数的情况下,构建一个新的最优时间表序列。根据干扰度量函数的不同研究了两个问题,第一个问题的目标函数是极小化总完工时间与总误工时间的加权和;第二个问题的目标函数是极小化总完工时间与总提前时间的加权和。对于所研究的问题,首先证明了最优排序具有的性质,然后建立了相应的拟多项式时间动态规划算法。
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| 关 键 词： | 排序 干扰管理 学习效应 退化工件 动态规划 |
| 收稿时间： | 2014-09-04 |
Disruption Management for Single Machine Scheduling with Learning and Deteriorating Effect |
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| LIU Chun-lai,WANG Jian-jun.Disruption Management for Single Machine Scheduling with Learning and Deteriorating Effect[J].Operations Research and Management Science,2019,28(1):94-100. |
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| Authors: | LIU Chun-lai WANG Jian-jun |
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| Affiliation: | 1.School of Management, Hangzhou Dianzi University, Hangzhou 310018, China; 2.Faculty of Management and Economics, Dalian University of Technology, Dalian 116023, China |
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| Abstract: | Aimed at the scheduling problem of machine availability constraint with learning and deteriorating effect, a predictable single machine disruption model is established. In the model, the processing time of a job is a function of its starting time and its position. Moreover, the machine could be unavailable for breakdown or periodic maintenance. Because of the machine disruption, the original schedule may become infeasible or too far from optimal. The objective is to create the new schedule that takes into account both the original objective function and a measure of deviation from the original schedule. Depending on the different measurement function, we study two versions of the problem. In the first one, the objective is weighted sum of total completion time and total tardiness while in the second one, the objective is weighted sum of total completion time and total earliness. For the problems, we first prove some properties of the optimal schedule and then dynamic programming algorithms are proposed. |
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| Keywords: | scheduling disruption management learning effect deteriorating jobs dynamic programming |
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