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This paper presents an efficient scheme to locate multiple peaks on multimodal optimization problems by
using genetic algorithms (GAs). The premature convergence problem shows due to the loss of diversity,
the multipopulation technique can be applied to maintain the diversity in the population and the
convergence capacity of GAs. The proposed scheme is the combination of multipopulation with adaptive
mutation operator, which determines two different mutation probabilities for different sites of the
solutions. The probabilities are updated by the fitness and distribution of solutions in the search space
during the evolution process. The experimental results demonstrate the performance of the proposed
algorithm based on a set of benchmark problems in comparison with relevant algorithms.
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