Tabu search method for solving multiobjective job shop scheduling problem

Abstract

Scheduling is widely studied and it involves of complex combinatorial optimization problems. A job shop scheduling problem (JSSP) is one of the common scheduling problems. The application of it ranges from manufacturing to services industries. It can be considered as a NP-hard problem. A lot of research has been performed in this particular area to obtain an effective schedule jobs for various objectives. More than one objective in a single problem is considered multiobjective problem. Two objectives, which are the maximum completion time (makespan) and total weighted tardiness, are measured simultaneously to improve the performance of the schedule. In this study, metaheuristic method known as tabu search algorithm is proposed to tackle the problem. But, first of all Giffler and Thompson (GT) algorithm will be applied to obtain the potential initial solution for the respective problem. Benchmark problem is used to evaluate and study the performance of the proposed algorithm. Results shows that tabu search provide a better solution compared to simulated annealing method.