Abstract
AbstractThis paper proposes a new approach to solve chance constrained problems (CCPs) efficiently. Specifically, the probabilistic constraint in CCP can be evaluated directly if the cumulative distribution function (CDF) of uncertain function value is known. Therefore, the CDF is approximated by using weighted empirical CDF (W ECDF). Then a powerful evolutionary algorithm, namely differential evolution, combined with W ECDF is used to solve CCP. In order to demonstrate the performance of the proposed method, it is applied to flood control planning problems.
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