Design of a Production System Using Genetic Algorithm

The primary objective of this paper is to develop a design methodology which addresses combinational complexity of CM design problem with non linear objectives of the mathematical model. In this paper, a mathematical model is first developed. It considers the part flow time between machines, processing time of the part, throughput of the plant. With these variables objective function were developed with constraints. Genetic Algorithm was employed as a part of heuristic which handles large CM design problem in a reasonable amount of time. Results from the genetic algorithm techniques were also compared with respect to the three objective function, mean flow time and throughput to the conventional technique. It has been found that the performance of GA offers comparatively better results in terms of minimum mean-flow time and maximum throughput. Furthermore, the problem discussed in this paper involves several variables and a multi-objective function, therefore the ability of GA to handle this type of objective functions and constraints make it a good approach to solve the problem. Finally, a graphical scheme has been used for a comparative study of all the techniques under each performance criterion. (C) 2014 Elsevier Ltd.