JSW 2006 Vol.1(2): 34-39 ISSN: 1796-217X
doi: 10.4304/jsw.1.2.34-39
doi: 10.4304/jsw.1.2.34-39
Variable Neighbourhood Search for Job Shop Scheduling Problems
Mehmet Sevkli1, M. Emin Aydin2
1Operation Research Department, Defense Sciences Institute, Turkish Military Academy 06654, Cankaya, Ankara
2University of Bedfordshire, Dept. of Computing and Information Systems Luton, UK
Abstract—Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for problem solving in which a systematic change of neighbourhood within a local search is carried out. In this paper, an investigation on implementing VNS for job shop scheduling problems is carried out tackling benchmark suites collected from OR library. The idea is to build the best local search and shake operations based on neighbourhood structure available. The results are presented and compared with the recent approaches in the literature. It is concluded that the VNS algorithm can generally find better results.
Index Terms—variable neighbourhood search, job shop scheduling
2University of Bedfordshire, Dept. of Computing and Information Systems Luton, UK
Abstract—Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for problem solving in which a systematic change of neighbourhood within a local search is carried out. In this paper, an investigation on implementing VNS for job shop scheduling problems is carried out tackling benchmark suites collected from OR library. The idea is to build the best local search and shake operations based on neighbourhood structure available. The results are presented and compared with the recent approaches in the literature. It is concluded that the VNS algorithm can generally find better results.
Index Terms—variable neighbourhood search, job shop scheduling
Cite: Mehmet Sevkli, M. Emin Aydin, " Variable Neighbourhood Search for Job Shop Scheduling Problems," Journal of Software vol. 1, no. 2, pp. 34-39, 2006.
General Information
ISSN: 1796-217X (Online)
Frequency: Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKI, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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