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Soft Computing

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31.10.2018 | Methodologies and Application

Optimisation of production scheduling for multi-product orders in VCIM systems using GA

verfasst von: Son Duy Dao, Kazem Abhary, Romeo Marian, Mark Goh

Erschienen in: Soft Computing | Ausgabe 20/2019

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Abstract

Virtual computer-integrated manufacturing (VCIM) is a global integrated manufacturing system which can exploit locally as well as globally distributed manufacturing resources. Production scheduling plays an important role in the success of a VCIM system. In this paper, an innovative genetic algorithm (GA) is developed to search for optimal/sub-optimal solutions to the production scheduling problem in VCIM systems. The developed GA has a unique chromosome representation, two modified crossovers, three modified mutations, dynamic ranking selection, adaptive stop-and-restart-with-memory mechanism, and a parameter set tuned by the response surface method. The effectiveness of the developed GA is validated through a comprehensive case study. The computational data from the case study show that the developed GA outperforms three commercial optimisation solvers. The outcomes of this research serve as a foundation towards a global decision support system that can help decision makers to operate VCIM systems more effectively.

Vorheriger Artikel The maximum points-based supervised learning rule for spiking neural networks

Nächster Artikel Improved harmony search with general iteration models for engineering design optimization problems

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Titel: Optimisation of production scheduling for multi-product orders in VCIM systems using GA
verfasst von: Son Duy Dao
Kazem Abhary
Romeo Marian
Mark Goh
Publikationsdatum: 31.10.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 20/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3578-y

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