期刊
ENGINEERING OPTIMIZATION
卷 36, 期 5, 页码 607-634出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03052150410001704845
关键词
artificial immune system; genetic algorithms; global optimization; parallel genetic algorithms
This paper proposes an algorithm based on a model of the immune system to handle constraints of all types (linear, nonlinear, equality, and inequality) in a genetic algorithm used for global optimization. The approach is implemented both in serial and parallel forms, and it is validated using several test functions taken from the specialized literature. Our results indicate that the proposed approach is highly competitive with respect to penalty-based techniques and with respect to other constraint-handling techniques which are considerably more complex to implement.
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