Production scheduling using adaptable fuzzy logic with genetic algorithms

Production scheduling for a flexible manufacturing environment must satisfy multiple conflicting criteria. Whilst estimation and modelling of capacity is facilitated by commercially available tools, the actual release strategy of orders into the system is still subject to considerable research as improved solutions over conventional dispatching heuristics are sought. An order release mechanism incorporating an adaptable fuzzy logic system enhanced by genetic algorithms is proposed. Through the use of fuzzy logic, the system can consider multiple criteria and rapidly determine solutions of consistently high quality. Adaptability ensures that the solution quality is maintained throughout the life of the system. The subsequent application of a genetic algorithm follows an efficient optimization path, since the initial solution derived through fuzzy logic is known to be good. The system developed, using the combined methodology, was tested on a discrete event simulation model and showed measurable benefits in schedule performance against commonly implemented dispatching heuristics.