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Details for article 41 of 67 found articles
| Title: |
Multi-objective optimization of manufacturing cell design |
| Author: |
Dimopoulos, C. |
| Appeared in: |
International journal of production research |
| Paging: | Volume 44 (2006) nr. 22 pages 4855-4875 |
| Year: |
2006-11-15 |
| Contents: |
Whereas the single-objective cell-formation problem has been studied extensively during the past decades, research on the multi-objective version of the problem has been relatively limited, despite the fact that it represents a more realistic modelling of the manufacturing environment. This article introduces multi-objective GP-SLCA, an evolutionary computation methodology for the solution of the multi-objective cell-formation problem. GP-SLCA is a hybrid algorithm, comprising of GP-SLCA, a genetic programming algorithm for the solution of single-objective cell-formation problems, and NSGA-II, a standard evolutionary multi-objective optimization technique. The proposed methodology is capable of providing the decision maker with a range of non-dominated solutions instead of a single compromise solution, which is usually produced as an outcome of alternative multi-objective optimization techniques. The application of multi-objective GP-SLCA is illustrated on a large-sized test problem taken from the literature. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 41 of 67 found articles
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