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.
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Wang, YM., Xiao, NF., Yin, HL., Hu, EL. (2007). A Novel Heuristic Approach for Job Shop Scheduling Problem. In: Preparata, F.P., Fang, Q. (eds) Frontiers in Algorithmics. FAW 2007. Lecture Notes in Computer Science, vol 4613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73814-5_24
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DOI: https://doi.org/10.1007/978-3-540-73814-5_24
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