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Soft Computing
Erschienen in: Soft Computing 12/2017

24.05.2016 | Foundations

Two new meta-heuristics for no-wait flexible flow shop scheduling problem with capacitated machines, mixed make-to-order and make-to-stock policy

verfasst von: Sana Abdollahpour, Javad Rezaian

Erschienen in: Soft Computing | Ausgabe 12/2017

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Abstract

This paper focuses on solving no-wait flexible flow shop scheduling problem with capacitated machines and mixed make-to-order and make-to-stock production management policy restrictions. The considered objective function is minimization of the sum of tardiness cost, weighted earliness cost, weighted rejection cost and weighted incomplete cost. Considering the literature, this problem is known as NP-hard. Hence, the cloudy-based simulated annealing (CSA) and artificial immune system are developed to solve the considered problem. Due to the fact that the parameters may influence the meta-heuristic algorithms, the parameters tuning is performed by Taguchi method. Finally, the performances of algorithms are evaluated by solving the randomly generated problems. Computational experiments show that the CSA algorithm obtains higher-quality solutions than another one.
Vorheriger Artikel Optimizing path real-time logic for unified real-time system
Nächster Artikel On congruences in weak implicative semi-lattices

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Metadaten
Titel
Two new meta-heuristics for no-wait flexible flow shop scheduling problem with capacitated machines, mixed make-to-order and make-to-stock policy
verfasst von
Sana Abdollahpour
Javad Rezaian
Publikationsdatum
24.05.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 12/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-016-2185-z

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