抄録
This paper proposes an adaptive genetic local search (aGLS) algorithm for effectively solving reliability optimization problems. The proposed aGLS hybridizes a local search technique and genetic algorithm (GA). The local search technique is incorporated into the GA loop and its scheme is adaptively regulated according to the change of the average fitness value at every generation in GA.
For more various comparisons with the proposed aGLS, conventional GLS algorithm with local search that does not use any adaptive scheme is also suggested. These two algorithms are tested and analyzed using two complex reliability optimization problems. Numerical result shows that the proposed aGLS outperforms the conventional HGA.
