An effective neighborhood search for scheduling in dual-resource constrained interval job shop with environmental objective
Deming Lei and
Xiuping Guo
International Journal of Production Economics, 2015, vol. 159, issue C, 296-303
Abstract:
In this study, scheduling problem in dual-resource constrained (DRC) job shop with interval processing time and heterogeneous resources is investigated. A lexicographical method is applied to minimize interval carbon footprint and makespan. A dynamical neighborhood search (DNS) is proposed, which is composed of two phases. Two-string representation is used and its chromosome consists of the operation-based string and the resource string. Several initial solutions are produced and improved in the first phase and only one solution is applied in the second phase. Four neighborhood structures and their dynamical transition mechanism are utilized to produce new solutions. DNS is tested on a number of instances and compared with other algorithms. Computational experiments show DNS can provide the promising results for the problem.
Keywords: Dynamical neighborhood search; Dual-resource constrained job shop; Scheduling; Interval carbon footprint (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0925527314002436
Full text for ScienceDirect subscribers only
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:eee:proeco:v:159:y:2015:i:c:p:296-303
DOI: 10.1016/j.ijpe.2014.07.026
Access Statistics for this article
International Journal of Production Economics is currently edited by Stefan Minner
More articles in International Journal of Production Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().