Abstract
In this paper, two novel, surrogate search spaces are presented which, when combined with Genetic Algorithms (GA’s), show much promise for sequencing and scheduling problems. In particular, GA’s based on the new “problem space” search space are developed for three important job shop scheduling problems. Computational experiments are conducted for each problem with encouraging results.
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© 1992 Springer-Verlag Berlin · Heidelberg
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Storer, R.H., Wu, S.D., Vaccari, R. (1992). Local Search in Problem and Heuristic Space for Job Shop Scheduling Genetic Algorithms. In: Fandel, G., Gulledge, T., Jones, A. (eds) New Directions for Operations Research in Manufacturing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77537-6_9
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DOI: https://doi.org/10.1007/978-3-642-77537-6_9
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