Integration of genetic algorithm, analytic hierarchy process and computer simulation for optimisation of operator allocation in manufacturing systems with weighted variables

Integration of genetic algorithm, analytic hierarchy process and computer simulation for optimisation of operator allocation in manufacturing systems with weighted variables

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Article ID: iaor2014546
Volume: 17
Issue: 3
Start Page Number: 318
End Page Number: 339
Publication Date: Mar 2014
Journal: International Journal of Logistics Systems and Management
Authors: , , ,
Keywords: heuristics: genetic algorithms, simulation, optimization
Abstract:

This paper presents an integrated analytic hierarchy process (AHP) genetic algorithm (GA) and computer simulation (CS) for the optimisation of operator allocation in cellular manufacturing systems (CMS) with weighted variables. This is a challenging issue in manufacturing systems in general and in CMS in particular. A computer simulation model which considers various operators layout is developed. GA is utilised for optimisations of results of various operators layout and AHP is utilised to define the weight of variables of fitness function for GA. Previous studies only utilise multivariate analysis methods, fuzzy C‐means and simulation, whereas this study uses an integrated GA, AHP and simulation for CMS with weighted variables. Also, previous CMS studies consider only one type of product whereas this study considers multi product CMS modelling through simulation. Moreover, more robust CMS assessment indicators are used in the proposed model. A practical case study illustrates the effectiveness and superiority of the proposed methodology.

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