Accuracy Comparison of Various Techniques to Solve Machine Layout Problem

Abstract

This research work presents the accuracy comparison of various techniques to solve machine layout problem in cellular manufacturing. Objective is to determine the layout of machines within the cells in a way that minimizes intra-cell material handling cost and time, so substantially reduces total manufacturing costs for manufacturing industries while satisfying no overlap and no duplication of machine constraints. Good layout of machines is important to reduce the total distance travelled by all parts and to improve the productivity of the shop. Genetic Algorithm and Greedy Algorithm is proposed to solve the problem taken from literature. Accuracy of proposed Genetic Algorithm, proposed Greedy Algorithm and various other techniques taken from literature is compared. Accuracy of Genetic Algorithm is found better compared to Greedy Algorithm and various other techniques taken from literature in all cases except one. Furthermore the results show that Genetic Algorithm is capable of finding out the multiple optimum solutions. The multiple solutions generated by Genetic Algorithm have more changes to satisfy the soft constraints of the machine layout problem and thus add no extra penalty to the cost of the machine layout compared to the single solution generated by any other techniques.