Adopted rescheduling strategy for solving the dynamic job shop using GA based Local Search

Abstract

In this paper, a rescheduling strategy based Genetic Algorithm and Tabu search is introduced to solve the dynamic job shop scheduling problem where the objective is to minimize the makespan ($C_{max}$). To evaluate the adopted methodology, numerical experiments have been designed to test the performance of the proposal. Yet, we have compared the obtained results with some common dispatching rules and meta-heuristic algorithm. Our proposal gives significant results in terms of minimum completion time(makespan).