Optimization in Manufacturing Systems Using Evolutionary Techniques

Abstract

This chapter introduces various types of manufacturing systems and different types of traditional and modern optimization techniques. Chapter briefs about evolutionary techniques such as Particle swarm optimization and Genetic algorithm to optimize the various kind of manufacturing system with an objective to overcome the limitations of traditional optimization techniques and to enhance the optimality of objective function. Besides that, customary methodology is to utilize an ordinary least squares relapse investigation for building up the machinability models. In recent decade, the utilization of evolutionary calculation techniques, or additionally called the Genetic strategies, in light of impersonation of Darwinian characteristic choice has turned out to be across the board. This is because of truth that numerous frameworks are excessively complex, making it impossible to be effectively enhanced by the utilization of traditional deterministic calculations. Despite what might be expected, the evolutionary algorithms (EA) include probabilistic tasks. The current chapter also presents brief details about stepwise procedure of implementation of genetic algorithm and particle swarm optimization to solve various problems associate with manufacturing systems.