Adaptive genetic algorithm for multi-peak searching
Xiufeng Wang · Control theory & applications · 2004
An adaptive multi-peak genetic searching strategy based on optimal subgroup migrating and the functional transformation is proposed. The main idea is, all peaks of multi-peak problems whose peaks are not equally high are transformed into those whose peaks are equally high by functional transformation so as to find all peaks in the same probability; Some genetic operators and near relative excluding strategy are executed in order to maintain the population diversity; The excellent individuals whose fitness are bigger than a threshold are migrated into a subpopulation; Gradient operator in subpopulation is applied to make the individuals evolved subtly. This searching strategy not only can ensure to find all peaks, but it doesnot need any pre-knowledge hypothesis, such as the number and distribution of the peaks. Finally, a comparison test with Spears' s Simple Sub Population strategy is performed.