Appropriate Evolutionary Algorithm for Scheduling in FMS

The diffusion of flexible manufacturing systems (FMS) has not only invigorated production systems, but has also given considerable impetus to relevant analytical fields like scheduling theory and adaptive controls. Depending on the demand of the job there can be variation in batch size. The change in the jobs depends upon the renewal rate. But this does not involve much change in the FMS setup. This paper obtains an optimal schedule of operations to minimize the total processing time in a modular FMS. The FMS setup considered here consists of four numbers of machines to accomplish the desired machining operations. The scheduling deals with optimizing the cost function in terms of machining time. The powers Evolutionary Algorithms, like genetic algorithm (GA) and simulated annealing (SA), can be beneficially utilized for optimization of scheduling FMS. The present work utilizes these powerful approaches and finds out their appropriateness for planning and scheduling of FMS producing variety of parts in batch mode.