Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems

Dao, Son Duy

ISBN 10: 3319891413 / ISBN 13: 9783319891415

Editore: Springer 2019-06, 2019

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Dati bibliografici

• Titolo: Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
• Editore: Springer 2019-06
• Data di pubblicazione: 2019
• Lingua: Inglese
• ISBN 10: 3319891413
• ISBN 13: 9783319891415
• Rilegatura: PF
• Condizione: New

Descrizione articolo

Riassunto

<p>This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.</p><p><b></b></p>

Dalla quarta di copertina

This thesis reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems. It also describes a robust genetic algorithm for production scheduling in VCIM systems. The model, which is the most comprehensive of its kind to date, is not only capable of supporting collaborative shipment scheduling and handling multiple product orders simultaneously, but also helps cope with multiple objective functions under uncertainties. In turn, the genetic algorithm, characterised by an innovative algorithm structure, chromosome encoding, crossover and mutation, is capable of searching for optimal/suboptimal solutions to the complex optimisation problem in the VCIM production- scheduling model described. Lastly, the effectiveness of the proposed approach is verified in a comprehensive case study.