Identification of a Heuristic Which Maximizes Percentage Utilization of Machines in a Job Shop Problem

This paper discusses a set of heuristic algorithms used to maximize the percentage utilization of machines in a Job shop scheduling (JSS) problem. Job shop scheduling environment consists of a set of machines and a collection of jobs to be scheduled. Each job consists of several operations with specified processing order. In this paper, Genetic Algorithm (GA), Simulated Annealing (SA) and Hybrid Simulated Annealing (HSA) algorithms are used for the objective measure of utilization of machines in Job Shop Model problem. These three algorithms are considered as different treatments of each problem and are compared. The conclusion is that percentage utilization of machine is maximum in most of the cases under Genetic Algorithm when compared with other two algorithms.