Multi-operator based biogeography based optimization with mutation for global numerical optimization

AbstractBiogeography based optimization (BBO) is a new evolutionary optimization based on the science of biogeography for global optimization. We propose two extensions to BBO. First, we propose a new migration operation based multi-parent crossover called multi-parent migration model, which is a generalization of the standard BBO migration operator. The new migration model can satisfy a balance of exploration and exploitation. Second, the Gaussian mutation operator is integrated into multi-operator biogeography based optimization (MOBBO) to enhance its exploration ability and to improve the diversity of population. Experiments have been conducted on 23 benchmark problems of a wide range of dimensions and diverse complexities. Simulation results and comparisons demonstrate the proposed MOBBO algorithm based multi-parent crossover model is better, or at least comparable to, the BBO, PBBO and evolutionary algorithms from literature when considering the quality of the solutions obtained