Iterative Genetic Algorithm for Task Scheduling in Non-Flexible Manufacturing Process

Abstract

Every manufacturing system has its increasing demand for well planned and scheduled operations for various products. A Genetic algorithm observed its great application for finding the best schedule for the flexible manufacturing System (FMS). But these flexible operations are having big limitations for real time processing in wide industries. Every real time operation demands non-flexibility with tasks dependent on each other, for this case the machine is fixed for a particular operation jointly called as Task. Hence, for this case we can generate the optimal solution showing the Tasks which can be executed in parallel. This paper gives an iterative genetic algorithm (IGA) for achieving solution for these limitations and to find optimum schedule for the various tasks to minimize the total makespan.