Adaptive Constrained Multi-Objective Biogeography-Based Optimization Based on Two-Stage Elite Selection

Abstract

a new adaptive constrained multi-objective biogeography-based optimization based on two-stage elite selection, ACMBBO, is proposed to solve constrained multi-objective optimization problems. According to the feature on constrained multi-objective and the evolutionary mechanism of BBO, the model of constrained multi-objective optimization which applies to BBO is built. In the model, the habitat suitability index, which combines with the degree of feasible and the Pareto dominance relation between the individuals, is redefined. Moreover, a new mechanism based on two-stage elite selection is set to preserve the elitist of population individuals. Also dynamic migration strategy is designed to improve the ability for exploitation and the utilization of the better individual. Numerical experiments have shown that ACMBBO is competitive with current other constrained multi-objective optimization algorithms on the convergence and the distribution, and is capable of solving the complex CMOPs more effectively and efficiently.