.png){kind=icon}
返回
A hybrid genetic algorithm for the resource-constrained project scheduling problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2006.12.033.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we propose a Hybrid Genetic Algorithm (HGA) for the Resource-Con strained Project Scheduling Problem (RCPSP). HGA introduces several changes in the GA paradigm: a crossover operator specific for the RCPSP; a local improvement operator that is applied to all generated schedules; a new way to select the parents to be combined; and a two-phase strategy by which the second phase re-starts the evolution from a neighbour's population of the best schedule found in the first phase. The computational results show that HGA is a fast and high quality algorithm that outperforms all state-of-the-art algorithms for the RCPSP known by the authors of this paper for the instance sets j60 and j120. And that it is competitive with other state-of-the-art heuristics for the instance set j30. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
project management
scheduling
heuristics
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
论文数:
2.2W
被引数:
6.4W
机构
暂无机构信息
引用论文
.png){kind=icon}
Solving the resource-constrained project problem by a variable neighbourhood scheduling search通过可变邻域调度搜索解决资源受限的项目问题
PREAI
分享收藏LSSPER: Solving the resource-constrained project scheduling problem with large neighbourhood searchLSSPER: 通过大邻域搜索解决资源受限的项目调度问题
PREAI
分享收藏
查看更多内容