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Production Engineering
Erschienen in: Production Engineering 4-5/2017

11.07.2017 | Production Management

A clonal selection algorithm for the generalized cell formation problem considering machine reliability and alternative routings

verfasst von: Bouchra Karoum, Youssef Bouazza Elbenani

Erschienen in: Production Engineering | Ausgabe 4-5/2017

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Abstract

The cell formation is the first step in the design of Cellular Manufacturing systems. It consists of grouping parts with similar processing needs into cells and identifying the set of machines needed to process these parts. The aim is to minimize the material handling costs and maximize the use of the machines. In this paper, the machine reliability and the alternative process routings are taken into account to form the production cells. The presence of these factors in addition to the production volume, operation sequence and production time makes the problem more realistic but also more complex. Most authors solve this kind of problems by mathematical programming approaches that require large amounts of computational efforts. Therefore, a modified version of the Clonal Selection Algorithm is introduced and a local search mechanism is adopted in this paper. The obtained results are compared with those of the Branch and Bound (B&B) method using LINGO software. The comparison reveals the effectiveness and the efficiency of the proposed method in terms of both solution quality and computation time required.
Vorheriger Artikel Implementation of Lean and Green practices: a supplier-oriented assessment method
Nächster Artikel A mathematical model for assessing the effects of a lot splitting feature on a dynamic cellular manufacturing system

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Metadaten
Titel
A clonal selection algorithm for the generalized cell formation problem considering machine reliability and alternative routings
verfasst von
Bouchra Karoum
Youssef Bouazza Elbenani
Publikationsdatum
11.07.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Production Engineering / Ausgabe 4-5/2017
Print ISSN: 0944-6524
Elektronische ISSN: 1863-7353
DOI
https://doi.org/10.1007/s11740-017-0751-6

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