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The paper presents a solution for the problem of choosing a method foranalytical determining of weight factors for a genetic algorithm additivefitness function. This algorithm is the basis for an evolutionary process,which forms a stable and effective query population in a search engine toobtain highly relevant results. The paper gives a formal description of analgorithm fitness function, which is a weighted sum of three heterogeneouscriteria. The selected methods for analytical determining of weight factors aredescribed in detail. It is noted that expert assessment methods are impossibleto use. The authors present a research methodology using the experimentalresults from earlier in the discussed project "Data Warehouse Support on theBase Intellectual Web Crawler and Evolutionary Model for Target InformationSelection". There is a description of an initial dataset with data ranges forcalculating weights. The calculation order is illustrated by examples. Theresearch results in graphical form demonstrate the fitness function behaviorduring the genetic algorithm operation using various weighting options.

Determination of weight coefficients for additive fitness function of genetic algorithm