Hybrid genetic approach for solving large-scale capacitated cell formation problems with multiple routings

• Published in: European journal of operational research Vol. 171; no. 3; pp. 1051 - 1070
• Main Authors: Nsakanda, Aaron Luntala, Diaby, Moustapha, Price, Wilson L.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 16-06-2006; Elsevier; Elsevier Sequoia S.A
• Series: European Journal of Operational Research
• Subjects: Alternate routings; Cellular manufacturing systems; Dantzig–Wolfe decomposition; Genetic algorithm; Genetic algorithms; Large-scale optimization; Manufacturing cells; Operations research; Optimization; Optimization techniques; Production planning; Routing; Studies; Cellular manufacturing systems; Alternate routings; Large-scale optimization; Genetic algorithm; Dantzig–Wolfe decomposition
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2005.01.017

We present a comprehensive model for designing a cellular manufacturing system. The model bridges several known problems in that it integrates the cell formation problem, the machine allocation problem, and the part routing problem. Multiple process plans for each part and multiple routing alternatives for each of those process plans are considered. The part demands can be satisfied from internal production or through outsourcing. Machines have limited capacities. We propose a solution methodology based on a combination of a genetic algorithm and large-scale optimization techniques. A computational study is conducted to evaluate the viability of our approach for solving large scale problems. A limited computational experiment involving smaller problems, that are special cases of our model, is also conducted to compare our solution approach with existing models.