  The paper presents a solution for the problem of choosing a method for
analytical determining of weight factors for a genetic algorithm additive
fitness function. This algorithm is the basis for an evolutionary process,
which forms a stable and effective query population in a search engine to
obtain highly relevant results. The paper gives a formal description of an
algorithm fitness function, which is a weighted sum of three heterogeneous
criteria. The selected methods for analytical determining of weight factors are
described in detail. It is noted that expert assessment methods are impossible
to use. The authors present a research methodology using the experimental
results from earlier in the discussed project "Data Warehouse Support on the
Base Intellectual Web Crawler and Evolutionary Model for Target Information
Selection". There is a description of an initial dataset with data ranges for
calculating weights. The calculation order is illustrated by examples. The
research results in graphical form demonstrate the fitness function behavior
during the genetic algorithm operation using various weighting options.
