A Genetic Algorithm for Solving the Integrated Cell Formation, Layout and Scheduling Problem

Cellular manufacturing systems (CMS) typically comprise a number of manufacturing cells served by a centralized material handling system. Designing such systems includes three major decisions; cell formation (CF), group layout (GL), and group scheduling (GS). Traditionally, these three decisions have been dealt with separately, which has usually lead to less than optimal system performance. In a previous paper, a mixed integer linear programming (MILP) model was proposed for solving the integrated CF, GL and GS problem, to efficiently design and operate CMSs. In this paper, an efficient Genetic Algorithm (GA) is proposed to determine the optimal cell formation, layout of machines and schedule of parts on the machines in a job shop setting, simultaneously. The GA chromosome is designed to represent the three decisions in a way that allows maximum design and operational flexibility. The performance of the algorithm is tested by solving two problems previously introduced in the literature considering two objectives; minimizing the makespan and minimizing the mean flow time in the system. The proposed algorithm obtained the optimal solutions for the two problems in a few seconds. Keywords—cellular manufacturing systems; cell formation; group scheduling; group layout; genetic algorithm