Stochastic single-machine scheduling with workload-dependent maintenance activities

IF 1.3 4区数学 Q2 MATHEMATICS, APPLIED

Optimization Letters Pub Date : 2024-03-11 DOI:10.1007/s11590-024-02102-3

Manzhan Gu, Weitao Yang, Peihai Liu

引用次数: 0

Abstract

This paper studies the stochastic single-machine scheduling problem with workload-dependent maintenance activities, in which the processing times of all jobs are independently subject to a common discrete distribution, and the aim is to find the optimal policy so as to minimize the expected total discounted holding cost. Based on the definition of Markov process, for each of the two cases with the discount rate being zero or a positive number, we present two dynamic programming algorithms to produce the optimal static policy and the optimal dynamic policy, respectively.

查看原文本刊更多论文

随工作量而定的维护活动的单机随机调度

本文研究了具有工作量依赖性维护活动的随机单机调度问题，在该问题中，所有作业的处理时间都是独立的，服从一个共同的离散分布，目的是找到最优策略，使预期总贴现持有成本最小。根据马尔可夫过程的定义，针对贴现率为零或正数的两种情况，我们提出了两种动态编程算法，分别生成最优静态策略和最优动态策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Optimization Letters 管理科学-应用数学

CiteScore

3.40

自引率

6.20%

发文量

116

审稿时长

9 months

期刊介绍： Optimization Letters is an international journal covering all aspects of optimization, including theory, algorithms, computational studies, and applications, and providing an outlet for rapid publication of short communications in the field. Originality, significance, quality and clarity are the essential criteria for choosing the material to be published. Optimization Letters has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time one of the most striking trends in optimization is the constantly increasing interdisciplinary nature of the field. Optimization Letters aims to communicate in a timely fashion all recent developments in optimization with concise short articles (limited to a total of ten journal pages). Such concise articles will be easily accessible by readers working in any aspects of optimization and wish to be informed of recent developments.