Job-Shop Scheduling by GA. A New Crossover Operator

Czesław Smutnicki () and Adam Tyński ()
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Czesław Smutnicki: Wrocław University of Technology
Adam Tyński: Wrocław University of Technology

A chapter in Operations Research Proceedings 2005, 2006, pp 715-720 from Springer

Abstract: Summary The new distance measure between job-shop solutions, based on Euclidean measure, has been proposed. The significant positive correlation of the proposed measure with its suitable version based on the Kendall’s tau measure has been revealed. By applying this measure, a new, easy tunable, crossover quasi-operator for the genetic approach is designed. The genetic algorithm, equipped with the new operator, has been applied to the job-shop scheduling problem with the sum of job completion times criterion. Results provided by the algorithm, compared with the best results known in the literature, confirm superiority of the proposed method.

Keywords: Genetic algorithms; Job-shop scheduling; Crossover operators (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-32539-0_112

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DOI: 10.1007/3-540-32539-5_112

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