In spite of many researches in literature investigating dynamic of cell formation (CF) problem, further research needs to be elaborated to assay hidden aspects of cellular manufacturing system (CMS), due to inherent complexity and uncertainty on optimizing this problem. In this paper, sensitivity analysis of modified self-adaptive differential evolution (MSDE) algorithm is proposed for basic parameters of CF problem, considering to the graphical representation supported by statistical analysis. Hence, a dynamic integer model of CF problem is first presented as the NP-hard problem. Then, the two basic test CF problems are introduced thereby the performance of MSDE algorithm assessed by diverse problems sizes through 140 runs from aspects of the average runtime of algorithm and the best local optimum objective function. Finally, statistical analysis is implemented on behavior of objective function values in order to validate our computational results graphically as well as statistically, giving some insights related to importance of CF parameters on designing CMS.

Sensitivity analysis of dynamic cell formation problem through meta-heuristic / Hassannezhad, Mohammad; Cantamessa, Marco; Montagna, Francesca; Mehmood, Fahad. - In: PROCEDIA TECHNOLOGY. - ISSN 2212-0173. - ELETTRONICO. - 12:(2014), pp. 186-195. (Intervento presentato al convegno 7th International Conference Interdisciplinarity in Engineering tenutosi a Romania nel 10-11 October 2013) [10.1016/j.protcy.2013.12.474].

Sensitivity analysis of dynamic cell formation problem through meta-heuristic

HASSANNEZHAD, MOHAMMAD;CANTAMESSA, Marco;MONTAGNA, FRANCESCA;MEHMOOD, FAHAD
2014

Abstract

In spite of many researches in literature investigating dynamic of cell formation (CF) problem, further research needs to be elaborated to assay hidden aspects of cellular manufacturing system (CMS), due to inherent complexity and uncertainty on optimizing this problem. In this paper, sensitivity analysis of modified self-adaptive differential evolution (MSDE) algorithm is proposed for basic parameters of CF problem, considering to the graphical representation supported by statistical analysis. Hence, a dynamic integer model of CF problem is first presented as the NP-hard problem. Then, the two basic test CF problems are introduced thereby the performance of MSDE algorithm assessed by diverse problems sizes through 140 runs from aspects of the average runtime of algorithm and the best local optimum objective function. Finally, statistical analysis is implemented on behavior of objective function values in order to validate our computational results graphically as well as statistically, giving some insights related to importance of CF parameters on designing CMS.
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2525510
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