Algorithm of global extremum search area definition for several variables function

Rustam G. Asadullaev, Vladimir V. Lomakin


The article is devoted to the problem of global extremum search for several variables function. A modified algorithm is developed for the search of global extremum function, based on evolutionary calculations and differing by the approach of an area development to create an initial population of agents. They developed the algorithm for the function extremum search area definition, which ultimately performs the decomposition of the research area into subsets. It is suggested to take into account the knowledge of an expert, an agent and the available group agents. Based on the available knowledge, the region is divided into three subsets with different priorities. At that, the possibility of the function extremum drift is taken into account and a separate procedure of a search area definition is implemented, taking into account the retrospective information on the drift of parameters.


multicriteria optimization, multiextremal function, global extremum, extremum drift, solution search area, decision support system

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