A Local Search Heuristic with Self-tuning Parameter for Permutation Flow-Shop Scheduling Problem

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Tarih

2009

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IEEE

Erişim Hakkı

info:eu-repo/semantics/openAccess

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Özet

In this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.

Açıklama

IEEE Symposium on Computational Intelligence in Scheduling -- MAR 30-APR 02, 2009 -- Nashville, TN

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Kaynak

2009 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN SCHEDULING: (CI-SCHED)

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N/A

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