A genetic-algorithm-based heuristic for the GT cell formation problem

This paper presents a heuristic for the machine-part grouping problem which incorporates relevant production requirements such as routing sequence, production volume, unit handling size, unit processing time and cell size. The heuristic consists of two phases. The first phase is developed based on a genetic algorithm and greedy heuristic to solve the machine grouping problem. Once machine cells are identified, the second phase is employed to identify the associated part families. The performance of the heuristic is examined through a comparative study with some existing solution methods. Global efficiency, group efficiency, intercell move factor and grouping effectiveness are adopted as comparative measures.