AN AUTOMATED TOOL FOR OPTIMIZING JOB SHOP SCHEDULING USING METAHEURISTICS

Growth and development of any nation is directly influenced by the health of manufacturing sector. Developments in the manufacturing industry serve as a reliable index that scales the development of a society. This paper summarizes the results of the research work with an aim to effectively schedule job shops. The primary objective of this work is to use meta-heuristics as a tool for optimizing the scheduling problem. In order to present the research to the user in the form of a tool a Graphical User Inter phase (GUI) is designed and presented. This tool provides the user with ease of use and flexibility in choosing a particular schedule. The GUI is coded using MATLAB. Three meta-heuristic approaches namely Particle Swarm Optimization (PSO), Chaotic Particle Swarm Optimization (CPSO), Genetic Algorithm (GA) are used to optimize the objective function and get an optimum schedule. The validity of the proposed methods is established by considering and analyzing the benchmark problems