.png){kind=icon}
返回
Branch, bound and remember algorithm for two-sided assembly line balancing problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ejor.2020.01.032.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This research presents a new branch, bound and remember (BBR) algorithm to minimize the number of mated-stations in two-sided assembly lines. The proposed methodology modifies the Hoffman heuristic to achieve high-quality upper bounds, and employs two new dominance rules, referred to as memory-based maximal load rule and memory-based extended Jackson rule, to prune the sub-problems. The BBR algorithm also employs several other improvements to enhance the performance, including renumbering the tasks and new lower bounds. Computational results demonstrate that BBR achieves the optimal solutions for all the tested instances within 1.0 s on average, including two optimal solutions for the first time. Comparative study shows that BBR outperforms the current best exact method (branch and bound algorithm) and the current best heuristic algorithm (iterated greedy search algorithm). As a consequence, the proposed BBR can be regarded as the state-of-the-art method for TALBP. (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
Combinatorial optimization
Assembly line balancing
Two-sided assembly line
Branch and bound
Branch, bound and remember
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
引用论文
.png){kind=icon}
Removal of rubidium ions by polyaniline nanocomposites modified with cobalt-Prussian blue analogues
PREAI
分享收藏
查看更多内容