Scheduling of flexible manufacturing systems using genetic algorithm: A heuristic approach

Abstract

Scheduling of production in Flexible Manufacturing Systems (FMSs) has been extensively investigated over the past years and it continues to attract the interest of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today's complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial schedule. Uncertainties in the production environment and modeling limitations inevitably result in deviations from the generated schedules. This makes rescheduling or reactive scheduling essential. One of the four different types of uncertainties that normally cause discrepancies between the actual output and the planned output is considered in this paper. These include unforeseen machine break-downs, increased order priority, rush orders arrival and order cancellations. In this paper, the current status of the shop is considered while rescheduling. The proposed algorithms revise only those operations that must be rescheduled and can, therefore, be used in conjunction with the existing scheduling methods to improve the efficiency of flexible manufacturing systems.