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Article type: Research Article
Authors: Yalaoui, Naim | Amodeo, Lionel | Yalaoui, Farouk | Mahdi, Halim
Affiliations: CAILLAU Company, Issy Les Moulineaux, France | ICD-LOSI, University of Technology of Troyes, Troyes, France
Note: [] Corresponding author. Naim Yalaoui, CAILLAU Company, 28, Rue Ernst Renan, Issy les Moulineaux, France. E-mails: [email protected] (Naim Yalaoui); [email protected] (Lionel Amodeo); [email protected] (Farouk Yalaoui); [email protected] (Halim Mahdi).
Abstract: In order to apply a continuous improvement of their production systems, all managers are always trying to improve their production systems by optimizing their scheduling method. This involves the search for efficient methods for obtaining the best results according to the costs and the delay criteria for example. This paper aims to solve a specific hybrid reentrant flow shop scheduling problem. This one contains some stages with some identical parallel machines. The orders sequenced are splited in batches. Each batch is processed one or more time on the system. For the resolution, various methods have been developed. An exact method which lists all the solutions and selects the best one and approximated methods such as the genetic algorithm (GA), the genetic algorithm under fuzzy controller (FLCGA), the particle swarm optimization (PSO) and the particle swarm optimization under fuzzy controller (FLCPSO). The results discussed in the paper are very interesting.
Keywords: Re-entrant scheduling, genetic algorithm, fuzzy logic, particle swarm optimization
DOI: 10.3233/IFS-130771
Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 3, pp. 1113-1121, 2014
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