Simple Feasibility Rules and Differential Evolution for Constrained Optimization

In this paper, we propose a differential evolution algorithm to solve constrained optimization problems. Our approach uses three simple selection criteria based on feasibility to guide the search to the feasible region. The proposed approach does not require any extra parameters other than those normally adopted by the Differential Evolution algorithm. The present approach was validated using test functions from a well-known benchmark commonly adopted to validate constraint-handling techniques used with evolutionary algorithms. The results obtained by the proposed approach are very competitive with respect to other constraint-handling techniques that are representative of the state-of-the-art in the area.

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