Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems

• Κύριος συγγραφέας: Dao, Son Duy (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Springer Theses, Recognizing Outstanding Ph.D. Research,
• Θέματα: Engineering economics.; Engineering economy.; Computational intelligence.; Manufactures.; Business logistics.; Engineering Economics, Organization, Logistics, Marketing.; Computational Intelligence.; Manufacturing, Machines, Tools, Processes.; Logistics.
• Φυσική περιγραφή: XVII, 147 p. 17 illus., 11 illus. in color. online resource.
• ISBN: 9783319721132
• ISSN: 2190-5053
• DOI: 10.1007/978-3-319-72113-2

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.