Hybrid branch and bound algorithms for the two-stage assembly scheduling problem with separated setup times
JianChao Luo,
ZhiQiang Liu and
KeYi Xing
International Journal of Production Research, 2019, vol. 57, issue 5, 1398-1412
Abstract:
This article proposes hybrid branch and bound algorithms to minimise the makespan for the two-stage assembly scheduling problem with separated setup times. In the studied problem, there are multiple machines at the first stage, each of which produces a component of a job. When all components are available, a single assembly machine at the second stage completes the job. Existing algorithms are based on the state space search and hence suffer from the state space explosion problem. In order to reduce the search space, lower and upper bounds for a partial schedule are proposed. Also, a heuristic function and a dominance rule are developed to guide the search process. Moreover, accelerated factors are introduced to increase the speed of the search. Experimental results indicate that our algorithms outperform an existing method, and can find the optimal or near-optimal schedules in a short time for all tested problems with up to ten thousand jobs and nine first-stage machines.
Date: 2019
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2018.1489156 (text/html)
Access to full text is restricted to subscribers.
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:taf:tprsxx:v:57:y:2019:i:5:p:1398-1412
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2018.1489156
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().