Details
Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
Springer Theses
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 27.12.2017 |
| ISBN/EAN: | 9783319721132 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<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>
Chapter 1: Introduction.- Chapter 2: Literature review.- Chapter 3: An innovative production scheduling model for VCIM systems.- Chapter 4: An innovative genetic algorithm for VCIM production scheduling optimisation.- Chapter 5: Case study.- Chapter 6: Conclusions and recommendations for future work.
<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>
Nominated as an outstanding PhD thesis by the University of South Australia, Adelaide Reports on an innovative production-scheduling model for virtual computer-integrated manufacturing (VCIM) systems Presents a robust genetic algorithm for optimising production scheduling in VCIM systems Includes supplementary material: sn.pub/extras
<div><p>Nominated as an outstanding PhD thesis by the University of South Australia, Adelaide</p> <p>Reports on an innovative production scheduling model for virtual computer-integrated manufacturing (VCIM) systems</p> <p>Presents a robust genetic algorithm for optimising production scheduling in VCIM systems</p></div><div><br/></div>
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