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Erschienen in: Journal of Intelligent Manufacturing 4/2015

01.08.2015

No-wait flexible flowshop with uniform parallel machines and sequence-dependent setup time: a hybrid meta-heuristic approach

verfasst von: Pezhman Ramezani, Meysam Rabiee, Fariborz Jolai

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 4/2015

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Abstract

According to the state of the art of no-wait scheduling problem, practitioners have mostly concentrated on pure no-wait flow shop scheduling problem. In the most real world production cases, flow shops operate with uniform parallel machines at each stage to eliminate or reduce the bottleneck stages with aim of enhancing the efficiency of production. This paper deals with a no-wait scheduling problem considering anticipatory sequence-dependent setup times on the flexible flow shop environment with uniform parallel machines. The objective is to find the sequence which minimizes maximum completion time of jobs (i.e. makespan). Since this problem is known to be NP-hard, we introduce a novel approach to tackle the problem. In the solution approach, firstly a heuristic formulation is used for objective function evaluation. Afterwards, principles of meta-heuristic algorithms namely invasive weed optimization, variable neighborhood search and simulated annealing algorithms are hybridized as solution method of the problem. In addition, a Taguchi method is employed for calibration of parameters and operators of the proposed hybrid meta-heuristic. Various computational experiments in two scales of small and large are established to illustrate the effectiveness and robustness of the proposed method. Finally, the experimental results revealed the superiority of the performance of the hybrid meta-heuristic in comparison with original ones singularly.

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Metadaten
Titel
No-wait flexible flowshop with uniform parallel machines and sequence-dependent setup time: a hybrid meta-heuristic approach
verfasst von
Pezhman Ramezani
Meysam Rabiee
Fariborz Jolai
Publikationsdatum
01.08.2015
Verlag
Springer US
Erschienen in
Journal of Intelligent Manufacturing / Ausgabe 4/2015
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI
https://doi.org/10.1007/s10845-013-0830-2

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