Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems
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Beschreibung
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.
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
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
Autor*in
Son Duy Dao
Themen in »Modelling and Intelligent Optimisation of Production Scheduling in VCIM Systems«
VCIM Production Scheduling Model Collaborative Shipment Scheduling Partner Selection Multiple Product Orders Multiple Objective Functions Stochastic Model Genetic Algorithm Unique Chromosome Encoding Innovative Algorithm Structure Adaptive Stop-and-Restart-with-Memory Mechanism Engineering Economics