Multi-objective genetic algorithm for cell formation problem considering cellular layout and operations scheduling

Abstract

Integrated design of cellular manufacturing (CM) systems consist of three major decisions: cell formation (CF), cellular layout (CL) and planning issues such as cellular scheduling (CS). This article presents a mathematical model to concurrently identify the formation of cells, cellular layout and the operations sequence with the objective of minimising total transportation cost of parts as well as minimising makespan. A multi-objective genetic algorithm (MOGA) is then developed to solve the problem. The proposed MOGA exploits a novel evolutionary process which enables it to efficiently find Pareto optimal solutions. Computational results show the advantages of the proposed integrated approach and the superiority of the proposed MOGA over some well-known multi-objective evolutionary algorithms.