Abstract
Scope of this paper is to investigate the applicability of Genetic Algorithms to the solution of Static Permutation Flowshop problem and to compare their performance with those obtained with Taboo Search Algorithms. Since in order to obtain good results with Genetic Algorithms (Gas) it is necessary to tune a set of parameters, then a second purpose of the study is to devise a methodology to perform this tuning. The methodology used is the “Response Surface Methodology”.
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© 1995 Springer-Verlag/Wien
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Sangalli, N., Semeraro, Q., Tolio, T. (1995). Performance of Genetic Algorithms in the Solution of Permutation Flowshop Problem. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_128
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_128
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
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