4.7 Article

An improved migrating birds optimisation for a hybrid flowshop scheduling with total flowtime minimisation

期刊

INFORMATION SCIENCES
卷 277, 期 -, 页码 643-655

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2014.02.152

关键词

Metaheuristics; Operations research; Scheduling; Hybrid flowshop

资金

  1. National Science Foundation of China [61174187]
  2. NSFC-MSRA joint program [60933012]
  3. Basic Scientific Research Foundation of Northeast University [N110208001]
  4. Starting Foundation of Northeast University [29321006]
  5. Science Foundation of Liaoning Province in China [2013020016]
  6. Program for New Century Excellent Talents in University [NCET-13-0106]
  7. Basic Scientific Research Foundation of State Key Laboratory of Synthetical Automation for Process Industries [2013ZCX01]
  8. Shandong Province Key Laboratory of Intelligent Information Processing and Network Security (Liaocheng University)

向作者/读者索取更多资源

Migrating birds optimisation (MBO) is a new nature-inspired metaheuristic for combinatorial optimisation problems. This paper proposes an improved MBO to minimise the total flowtime for a hybrid flowshop scheduling problem, which has important practical applications in modern industry. A diversified method is presented to form an initial population spread out widely in solution space. A mixed neighbourhood is constructed for the leader and the following birds to easily find promising neighbouring solutions. A leaping mechanism is developed to help MBO escape from suboptimal solutions. Problem-specific heuristics and local search procedures are added to enhance the MBO's intensification capability. Extensive comparative evaluations are conducted with seven recently published algorithms in the literature. The results indicate that the proposed MBO is effective in comparison after comprehensive computational and statistical analyses. (C) 2014 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据