期刊
APPLIED SOFT COMPUTING
卷 9, 期 2, 页码 817-823出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.asoc.2008.05.008
关键词
Evolutionary algorithms; Multi-objective optimization; Liquid composite moulding
资金
- National Sciences and Engineering Research Council of Canada
- Fonds Quebecois de Recherche sur la Nature et les Technologies
A multi-objective evolutionary algorithm is applied to the problem of optimal gate location in liquid composite moulding. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is implemented and the efficiency of different variation operators is assessed on a benchmark problem, i.e., a mould of simple geometry. Following this, the algorithm is applied to a more complex mould geometry with the best variation operators. It is shown that the sole use of mutation proved better in the case of a complex part, whereas crossover proved helpful only for a simpler geometry. (C) 2008 Elsevier B. V. All rights reserved.
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