Chaos genetic searching algorithm for bilevel multi-objective programming problems and its applications
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摘要: 針對求解一類二層多目標規劃問題,首先將其轉化為等價的單目標規劃問題,然后利用遺傳算法優化的反演性和混沌優化方法的遍歷性,并結合精確罰函數求解非線性約束優化問題,提出了求解此類問題的混沌遺傳算法.該方法能夠有效改善遺傳算法的局部搜索能力和搜索精度,求解精度和可靠性較高.實際算例表明,算法是有效可行的.Abstract: A class of bilevel multl-objective programming was converted into the problem of equivalent single-level multi-objective programming. Then a new chaos genetic optimization algorithm was presented by using the inversion property of genetic algorithm and the ergodic property of chaos optimization method and combining with the exact l1 penalty function. The local search ability and search accuracy of genetic algorithm were improved. The solving accuracy and credibility became high. An actual calculated example showed that the algorithm is effective and efficient.
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