Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs
Shijin Wang,
Zhanguo Zhu,
Kan Fang,
Feng Chu and
Chengbin Chu
International Journal of Production Research, 2018, vol. 56, issue 9, 3173-3187
Abstract:
We consider a two-machine permutation flow shop scheduling problem to minimise the total electricity cost of processing jobs under time-of-use electricity tariffs. We formulate the problem as a mixed integer linear programming, then we design two heuristic algorithms based on Johnson’s rule and dynamic programming method, respectively. In particular, we show how to find an optimal schedule using dynamic programming when the processing sequence is fixed. In addition, we propose an iterated local search algorithm to solve the problem with problem-tailored procedures and move operators, and test the computational performance of these methods on randomly generated instances.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2017.1401236 (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:56:y:2018:i:9:p:3173-3187
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2017.1401236
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 ().