This paper presents a hybrid memetic algorithm for finding a conditional global extremum of functions. The algorithm combines such characteristics as modularity and adaptability which provides flexibility and controllability of the algorithm and reduces the influence of parameters. On the basis of the proposed algorithm the software complex is formed in the C# language. The method effectiveness is demonstrated on several well-known model examples of finding a conditional global extremum for functions of several variables.


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    Title :

    MODULAR HYBRID MEMETIC ALGORITHM FOR FINDING A CONDTIONAL GLOBAL EXTREMUM FOR FUNCTIONS OF SEVERAL VARIABLES


    Contributors:


    Publication date :

    2016



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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