An ACO-based hyperheuristic with dynamic decision blocks for intercell scheduling

Yunna Tian (), Dongni Li (), Pengyu Zhou (), Rongtao Guo () and Zhaohe Liu ()
Additional contact information
Yunna Tian: Beijing Institute of Technology
Dongni Li: Beijing Institute of Technology
Pengyu Zhou: Beijing Institute of Technology
Rongtao Guo: Beijing Institute of Technology
Zhaohe Liu: Beijing Institute of Technology

Journal of Intelligent Manufacturing, 2018, vol. 29, issue 8, No 14, 1905-1921

Abstract: Abstract In real production of equipment manufacturing industry, coordination between cells is needed. Intercell scheduling therefore comes into being. In this paper, a limited intercell transportation capacity constraint is taken into consideration, a hyperheuristic is proposed, which employs ant colony optimization to select appropriate heuristic rules for production scheduling and transportation scheduling. Moreover, dynamic decision blocks are introduced to the hyperheuristic to make a better balance between optimization performance and computation efficiency. Computational results show that, as compared with other approaches, the proposed approach performs much better with respect to minimizing total weighted tardiness while retaining low computational costs, and it is especially suitable for the problems with large sizes.

Keywords: Intercell scheduling; Transportation capacity; Decision block; Hyperheuristic (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-016-1216-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:29:y:2018:i:8:d:10.1007_s10845-016-1216-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-016-1216-z

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().