Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems

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.

Table des matières

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.

Résumé

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.

Détails du produit

• Auteurs: Son Duy Dao
• Edition: Springer, Berlin
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 01.01.2018
• EAN: 9783319721125
• ISBN: 978-3-31-972112-5
• Pages: 147
• Dimensions: 159 mm x 245 mm x 13 mm
• Poids: 368 g
• Illustrations: XVII, 147 p. 17 illus., 11 illus. in color.
• Thèmes: Springer Theses; Springer Theses
• Catégories: Sciences naturelles, médecine, informatique, technique > Technique > Autres; B, Artificial Intelligence, Fertigungstechnik und Ingenieurwesen, Distributions-, Lager- und Logistikmanagement, engineering, Operations Management, Logistics, Manufactures, Management of specific areas, Manufacturing, Machines, Tools, Processes, Engineering economy, Production engineering, Machines, Tools, Processes, Engineering Economics, Organization, Logistics, Marketing, Engineering economics, Industrial Management, Computational Intelligence, Distribution & logistics management, Business logistics