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.

[1]  Rakesh Nagi,et al.  An efficient heuristic in manufacturing cell formation for group technology applications , 1990 .

[2]  John McAuley,et al.  Machine grouping for efficient production , 1972 .

[3]  T. Narendran,et al.  A genetic algorithm approach to the machine-component grouping problem with multiple objectives , 1992 .

[4]  M. Chandrasekharan,et al.  ZODIAC—an algorithm for concurrent formation of part-families and machine-cells , 1987 .

[5]  M. Chandrasekharan,et al.  MODROC: an extension of rank order clustering for group technology , 1986 .

[6]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[7]  Tarun Gupta,et al.  Production data based similarity coefficient for machine-component grouping decisions in the design of a cellular manufacturing system , 1990 .

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  G. Srinivasan,et al.  GRAFICS—a nonhierarchical clustering algorithm for group technology , 1991 .

[10]  Richard Shell,et al.  Manufacturing system cell formation and evaluation using a new inter-cell flow reduction heuristic , 1992 .

[11]  D. A. Milner,et al.  Direct clustering algorithm for group formation in cellular manufacture , 1982 .

[12]  N. Singh,et al.  Design of cellular manufacturing systems: An invited review , 1993 .

[13]  J. King.  Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm , 1980 .

[14]  Paul J. Schweitzer,et al.  Problem Decomposition and Data Reorganization by a Clustering Technique , 1972, Oper. Res..