LAUSR

Virtual computer-integrated manufacturing (VCIM) is a global integrated manufacturing system which can exploit locally as well as globally distributed manufacturing resources. Production scheduling plays an important role in the success of a VCIM system. In this paper, an innovative genetic algorithm (GA) is developed to search for optimal/sub-optimal solutions to the production scheduling problem in VCIM systems. The developed GA has a unique chromosome representation, two modified crossovers, three modified mutations, dynamic ranking selection, adaptive stop-and-restart-with-memory mechanism, and a parameter set tuned by the response surface method. The effectiveness of the developed GA is validated through a comprehensive case study. The computational data from the case study show that the developed GA outperforms three commercial optimisation solvers. The outcomes of this research serve as a foundation towards a global decision support system that can help decision makers to operate VCIM systems more effectively.