A New Combined Approach for Optimizing Makespan in Job Shop Scheduling Problem

Abstract

Scheduling is the most important issue to be solved in the real time environment. One such emerging problem in the scheduling is the job shop scheduling problem, applied in various fields of engineering. Recently many works have been reported to reduce the makespan time in JSP. No Scheduling technique has guaranteed optimality. This paper aims at providing a well optimized scheduling technique, reducing the makespan based on precedence and capacity constraints allowing a machine to process almost one operation at a time. This paper proposed a Genetic algorithm with unordered subsequence Exchange cross-over (USXX) and Hybrid approach called a PSO-GA. The proposed algorithm is examined by using a set of benchmark instances with various sizes. The hybrid approach produced the better computational time with minimum iterations compare to the other existing algorithms.