OPTIMIZATION OF MARKETING STRATEGIES IN THE AGRO-INDUSTRIAL COMPLEX OF KAZAKHSTAN BASED ON A HYBRID METHOD

Оптимизация маркетинговых стратегий в АПК Казахстана на основе гибридного метода

Authors

DOI:

https://doi.org/10.26577/jpcsit2025335

Keywords:

agro-industrial complex (AIC), digital marketing, agromarketing, strategy, target functions, optimization, hybrid method, machine learning, models, agricultural products

Abstract

In the development of the agro-industrial complex (AIC) of the Republic of Kazakhstan, one of the key aspects is the improvement of information and consulting activities of enterprises and companies in the agricultural sector, in particular, aimed at increasing the efficiency of production and marketing of agricultural products. A significant aspect is also the development of agromarketing in the AIC, which will ultimately improve market mechanisms and increase the competitiveness of products of local agricultural producers. The study proposes a hybrid method for solving the problem of multi-criteria optimization of marketing strategies in the AIC. The method combines the use of the NSGA-II algorithm and machine learning based on K-means to analyze the results. The quality of the solution was assessed using the hypervolume parameters and visualization of the found optimal strategies using the Pareto front. The theoretical and practical significance of the study is confirmed by the possibility of adapting the proposed hybrid method for enterprises of the AIC of Kazakhstan, taking into account existing regional restrictions.

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Author Biographies

Zhansaya Abildaeva, Kazakh National Technical Research University named after K. I. Satbayeva, Almaty, Kazakhstan

Zh.T. Abildayeva – first author, 3rd year doctoral student of the “Software engineering” program, Department of Software Engineering, Kazakh National Technical Research University named after K. I. Satbayeva, Almaty, 050013, Kazakhstan.

Raissa Uskenbayeva, Kazakh National Technical Research University named after K. I. Satbayeva, Almaty, Kazakhstan

R.K. Uskenbayeva - Corresponding author, Professor, Vice-Rector of the Kazakh National Technical Research University named after K. I. Satbayeva, Almaty, 050013, Kazakhstan.

Nurbek Konyrbaev, Institute of Engineering and Technology, Korkyt Ata Kyzylorda University, Kyzylorda, Kazakhstan

N.B. Konyrbayev - Corresponding Author, Professor of the Department of Computer Science, PhD, Institute of Engineering and Technology, Korkyt Ata Kyzylorda University, Aiteke Bi Street. 29a, Kyzylorda 120014, Kazakhstan.

Gulzhanat Beketova, Almaty University of Energy and Communications G. Daukeeva, Almaty, Kazakhstan

G.S. Beketova - author, PhD, Almaty University of Energy and Communications named after Gumarbeka Daukeeva, department - "IT-engineering and artificial intelligence", position - associate professor.

Valery Lakhno, National University of Life and Environmental Sciences of Ukraine, Ukraine

Valerii Lakhno - Professor of the Department of Computer Systems, Networks and Cybersecurity, National University of Life and Environmental Sciences of Ukraine, Ukraine.email: lva964@nubip.edu.ua

Alona Desiatko, State University of Trade and Economics, Ukraine

Desyatko -PhD, Associate Professor at the Department of Software Engineering and Cyber Security State University of Trade and Economics. Her research focuses on developing models to understand and analyze the dynamics and interactions within economic and financial systems. Among her other areas of research are cloud technologies, information systems, cybersecurity, Product IT, Project IT, software architecture. She can be contacted on this email address, desyatko@gmail.com

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How to Cite

Abildaeva, Z., Uskenbayeva, R., Konyrbaev, N., Beketova, G., Lakhno, V., & Desiatko, A. (2025). OPTIMIZATION OF MARKETING STRATEGIES IN THE AGRO-INDUSTRIAL COMPLEX OF KAZAKHSTAN BASED ON A HYBRID METHOD: Оптимизация маркетинговых стратегий в АПК Казахстана на основе гибридного метода. Journal of Problems in Computer Science and Information Technologies, 3(3), 44–51. https://doi.org/10.26577/jpcsit2025335