A New Self-adaption Differential Evolution Algorithm Based Component Model

Finding a solution to constrained optimization problems (COPs) with differential evolution (DE) is a promising research issue. This paper proposes a novel algorithm to improve the original mutation and selection operators of DE. It explored some benefits from the component model and self-adaption mechanism, while solving the constrained optimization problems. Six benchmark functions about constraint problems are used in the experiment to evaluate the performance of the proposed algorithm. The experiment results demonstrate its effectiveness compared with other the current state-of-the art approaches in constraint optimization such as KM, SAFF and ISR.

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