Abstract
In this paper, an adaptive hybrid genetic algorithm with modified cuckoo search (MCS-AHGA) is proposed for effectively solving reliability optimization problems. For the proposed MCS-AHGA, a modified cuckoo search (MCS) which improves a weakness of conventional cuckoo search (CS) is adapted, and the genetic algorithm with an adaptive search scheme (AGA) is used. Hybridizing the MCS and the AGA can reinforce search quality and speed toward global optimal solution rather than hybridizing conventional CS and GA does. In numerical experiment, three types of reliability optimization problems are used for comparing the performance of the proposed MCS-AHGA with those of various conventional competing approaches including CS and GA. The experimental result proves that the proposed MCS-AHGA outperforms the competing conventional algorithms.
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