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.
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