A novel heuristic approach for job shop scheduling problem

Authors:
Yong-Ming Wang;Nan-Feng Xiao;Hong-Li Yin;En-Liang Hu
Affiliations:
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China and Department of Computer Science, Qujing Normal University, Qujing, China;School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science and Information Technology, Yunnan Normal University, Kunming, China;School of Mathematics, Yunnan Normal University, Kunming, China
Venue:
FAW'07 Proceedings of the 1st annual international conference on Frontiers in algorithmics
Year:
2007

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Abstract

Job shop scheduling problem has earned a reputation for being difficult to solve. Varieties of algorithms are employed to obtain optimal or near optimal schedules. Optimization algorithms provide optimal results if the problems to be solved are not large. But most scheduling problems are NP-hard, hence optimization algorithms are ruled out in practice. The quality of solutions using branch and bound algorithms depends upon the good bound that requires a substantial amount of computation. Local search-based heuristics are known to produce decent results in short running times, but they are susceptible to being stuck in local minima. Therefore, in this paper, we presented a brand-new heuristic approach for job shop scheduling. The performance of the proposed method was validated based on some benchmark problems of job shop scheduling, with regard to both solution quality and computational time.