Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints

Chettha Chamnanlor, Kanchana Sethanan (), Mitsuo Gen and Chen-Fu Chien
Additional contact information
Chettha Chamnanlor: Khon Kaen University
Kanchana Sethanan: Khon Kaen University
Mitsuo Gen: Tokyo University of Science
Chen-Fu Chien: National Tsing Hua University

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 8, No 10, 1915-1931

Abstract: Abstract This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling problem with time window constraints (RHFSTW), which is often found in manufacturing systems producing the slider part of hard-disk drive products, in which production needs to be monitored to ensure high quality. For this reason, production time control is required from the starting-time-window stage to the ending-time-window stage. Because of the complexity of the RHFSTW problem, in this paper, genetic algorithm hybridized ant colony optimization (GACO) is proposed to be used as a support tool for scheduling. The results show that the GACO can solve problems optimally with reasonable computational effort.

Keywords: Reentrant flexible flow shop; Time window; Hybrid genetic algorithm; Ant colony optimization; Local search (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/s10845-015-1078-9 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:28:y:2017:i:8:d:10.1007_s10845-015-1078-9

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

DOI: 10.1007/s10845-015-1078-9

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 ().