.png){kind=icon}
返回
A differential evolution algorithm for the customer order scheduling problem with sequence-dependent setup times
.png){kind=icon}
OA
AI
DOI：10.1016/j.eswa.2021.116097.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Although the customer order scheduling problem to minimize the total completion time has received a lot of attention from researchers, the literature has not considered so far the case where there are sequence-dependent setups between jobs belonging to different orders, a case that may occurs in real-life scenarios. For this NP-hard problem we develop a novel efficient approximate solution procedure. More specifically, we develop an innovative discrete differential evolution algorithm where differential mutations are performed directly in the permutation space and that uses a novel, parameter-free, restart procedure. The so-obtained solutions are improved by two proposed local search mechanisms that employ problem-specific, heuristic dominance relations. We carry out an extensive computational experience with randomly generated test instances to compare our proposal with existing algorithms from related problems. In these experiments, the proposed algorithm obtains the best results in terms of their average relative percentage deviation and success rate. Furthermore, an analysis of variance test, followed by a Tukey's test, confirms the excellent performance of the algorithm proposed.
Keyword:
Customer order scheduling
Production sequencing
Assembly scheduling problems
Total completion time
Metaheuristics
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:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
.png){kind=icon}
A differential evolution algorithm with self-adapting strategy and control parameters一种具有自适应策略和控制参数的差分进化算法
PREAI
分享收藏
分享收藏
查看更多内容