2026, Vol. 13, No. 2. - go to content...

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DOI: 10.15862/03INOR226 (https://doi.org/10.15862/03INOR226)

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Simagina S.G., Laznov I.S. Development of an algorithm and modeling of the process of selecting and coordinating a tour using artificial intelligence. Russian journal of resources, conservation and recycling. 2026; 13(2). Available at: https://resources.today/PDF/03INOR226.pdf (in Russian). DOI: 10.15862/03INOR226

Development of an algorithm and modeling of the process of selecting and coordinating a tour using artificial intelligence

Simagina Svetlana Germanovna
Povolzhskiy State University of Telecommunications and Informatics, Samara, Russia
E-mail: simaginasve@gmail.com
ORCID: https://orcid.org/0000-0001-8550-546X
RSCI: https://elibrary.ru/author_profile.asp?id=134189

Laznov Ilya Sergeevich
Povolzhskiy State University of Telecommunications and Informatics, Samara, Russia
E-mail: ilia_laznov@mail.ru
RSCI: https://elibrary.ru/author_profile.asp?id=1342489

Abstract. This article examines an approach to tour selection and approval using an intelligent decision-making module. The relevance of this topic is driven by the growing need for individualized travel products to ensure maximum satisfaction while minimizing service time.

The most effective solution to these problems is possible through the digital transformation of business processes, which is based on modeling. Two algorithms are considered for tour selection by a travel agent: one traditionally (with manual distribution) and the other using an intelligent decision-making module. The second algorithm requires some adjustments to the system, namely, optimization of iterative tour selection cycles, clarification of requirements, and automation of availability checks. An intelligent module is used to address these issues. To describe changes in the indicators of the tour selection and approval business process, distribution laws were defined, allowing for the most accurate description of the statistical data for this business process, obtained through an experiment. Based on the algorithms developed by the authors, a simulation modeling of the business process was conducted, in which the obtained distribution laws were applied to the main parameters. Request processing time was the key performance indicator for the system.

The simulation showed that the use of the intelligent module eliminated the travel agency’s main bottleneck — the manual consultation process. Request processing time was reduced by 28 %, and the frequency of re-approval cycles was also reduced by 15 %.

Keywords: business process; algorithm; intelligent module; distribution laws; simulation model; automation of tour selection and approval