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A novel differential evolution for constrained optimization

A novel differential evolution with coevolution (CDE) for constrained optimization problems (COPs) is proposed in this paper. The proposed CDE treats a COP as a bi-objective optimization problem where the first objective remains the same objective function itself while the second objective accounts for the degree of constraint violations. It adopts a simple and straightforward idea to solve COPs by dividing the whole population into dual subpopulations based on their feasibility. Each subpopulation corresponds with only one objective alone. An information-sharing strategy is incorporated to exchange search information between the different subpopulations. The comparison of the proposed approach with selected state-of-the-art constraint handling techniques demonstrates on a number of benchmark problems that the proposed framework performs competitively and effectively.