.png){kind=icon}
返回
Two branch-and-bound algorithms for the robust parallel machine scheduling problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cor.2011.09.019.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Uncertainty is an inevitable element in many practical production planning and scheduling environments. When a due date is predetermined for performing a set of jobs for a customer, production managers are often concerned with establishing a schedule with the highest possible confidence of meeting the due date. In this paper, we study the problem of scheduling a given number of jobs on a specified number of identical parallel machines when the processing time of each job is stochastic. Our goal is to find a robust schedule that maximizes the customer service level, which is the probability of the makespan not exceeding the due date. We develop two branch-and-bound algorithms for finding an optimal solution: the two algorithms differ mainly in their branching scheme. We generate a set of benchmark instances and compare the performance of the algorithms based on this dataset. (C) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Robust scheduling
Identical parallel machines
Stochastic processing times
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.3
论文数:
6.5K
被引数:
1.8W
机构
引用论文
.png){kind=icon}
A column generation based decomposition algorithm for a parallel machine just-in-time scheduling problem基于列生成的并行机实时调度分解算法
OAAI
OAAI分享收藏
查看更多内容