Gribanova E.B.Tomsk State University of Control Systems and Radioelectronics, Tomsk, Russian Federation katag@yandex.ru
Importance The article addresses optimization of marketing activities in social networks, particularly, the determination of groups for advertising based on its cost and characteristics that determine information dissemination about products and services among users. Objectives The aims are to develop a model to select groups of a social network for advertising, to modify and implement stochastic algorithms to solve the integer programming problems and compare their characteristics. Methods To develop optimization models, I use methods of operations research. The study also employs methods of random search for boundary points to solve the problem of integer programming, in particular, a simple random search, adaptive search and a search with varying probabilities. The multidimensional comparative analysis is applied to formulate integral characteristics of arguments that are used in the adaptive search algorithm. Results I developed models to select groups of social network for advertising, modified the adaptive search algorithm for boundary points, implying the calculation of an integral indicator of each variable in the problem based on normalized values, performed computational experiments and comparison of results obtained through the considered algorithms. The most accurate solution is obtained using the adaptive algorithm; the simplest to implement is a random search algorithm. Conclusions Economic agents may use the developed models to select groups of social network for advertising. The presented modification of adaptive search algorithm enables to solve integer programming problems.
Keywords: integer programming, social network, advertising, random search
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