.png){kind=icon}
返回
Solution algorithms for the makespan minimization problem with the general learning model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cie.2008.07.019.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Most of the papers devoted to scheduling problems with the learning effect concern the Wright's learning curve. On the other hand, the study about learning has pointed out that the learning curve in practice is very often an S-shaped function, which has not been considered in scheduling. Thus, in this paper, a single processor makespan minimization problem with an S-shaped learning model is investigated. We prove that this problem is strongly NP-hard even if the experience provided by each job is equal to its normal processing time. Therefore, to solve this problem, we prove some eliminating properties that are used to construct a branch and bound algorithm and some fast heuristic methods. Since the proposed algorithms are dedicated for the general case, i.e., where job processing times are arbitrary non-increasing experience dependent functions, their efficiency is verified numerically for the S-shaped model. (C) 2008 Elsevier Ltd. All rights reserved.
Keyword:
Scheduling
Learning effect
Single processor
Computational complexity
Branch and bound
Heuristic
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
IF:
6.5
论文数:
1.0W
被引数:
3.8W
机构
引用论文
.png){kind=icon}
分享收藏
分享收藏
查看更多内容