Multi-criterion Tackling Bottleneck Machines and Exceptional Parts in Cell Formation Using Genetic Algorithms
In this paper a Multi-criterion Decision Making (MCDM) model is introduced to tackle bottleneck machines and exceptional parts in manufacturing cell formation. In a given part-machine grouping scheme, bottleneck machines can be eliminated through machine duplication and exceptional parts may be removed by means of subcontracting. The developed multi-criterion model simultaneously takes into account 4 conflicting criteria regarding: inter-cell part movement, total cost of machine duplication and part subcontracting, overall utilization of the cells, and imbalance of the workloads among the cells. A Multi-objective Genetic Algorithm (MOGA) is then developed to seek for non-dominated or non-inferior solutions to assist the decision maker in his/her final selection. Comparative results in a number of cell formation problems show promising capabilities of the proposed solution approach.
KeywordsCellular Manufacture Cellular Manufacturing System Cell Formation Problem Reference Algorithm Bottleneck Machine
Unable to display preview. Download preview PDF.
- 4.Seifoddini H, (1989) Duplication process in machine cells formation in group technology. HE Transactions, 21(4): 382–388.Google Scholar
- 8.Burbidge JL, (1969) An introduction of group technology. Proc. Seminar on GT, Turin, Italy.Google Scholar
- 12.Schaffer JD, (1985) Multiple objective optimization with vector evaluated genetic algorithms. Proc. 1st Int. Conf. Genetic Algorithms and their Applications, Carnegie-Mellon University, Pittsburgh, USA: 93–100.Google Scholar
- 13.Horn J, Nafpliotis N, (1993) Multiobjective optimization using the niched pareto genetic algorithm. IlliGAL Report 93005, Illinois Genetic Algorithms Laboratory, University of Illinois, Urbana Champaign.Google Scholar