Journal
ENGINEERING OPTIMIZATION
Volume 36, Issue 5, Pages 607-634Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/03052150410001704845
Keywords
artificial immune system; genetic algorithms; global optimization; parallel genetic algorithms
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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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