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An approach to chance constrained problems using weighted empirical distribution and differential evolution with application to flood control planning
Author(s) -
Tagawa Kiyoharu,
Miyanaga Shun
Publication year - 2019
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.12148
Subject(s) - empirical distribution function , differential evolution , constraint (computer aided design) , mathematical optimization , probabilistic logic , cumulative distribution function , mathematics , function (biology) , differential (mechanical device) , computer science , probability density function , statistics , engineering , aerospace engineering , geometry , evolutionary biology , biology
This 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.