STAGES OF STRATEGIC PLANNING AND ORGANIZATION OF TOURIST AGGLOMERATIONS IN THE REGION

Аннотация

The optimal placement of tourist agglomerations within a region is a critical decision-making process that combines economic, environmental, and social considerations. This study explores algorithmic approaches to identifying and selecting optimal locations for tourist hubs, aiming to maximize visitor satisfaction, regional economic growth, and sustainability. Keywords: Optimal placement, Tourist agglomerations, Regional planning, Geographic Information Systems (GIS), Clustering algorithms, Genetic algorithms, Multi-criteria decision-making, Tourism infrastructure, Sustainability, Spatial optimization Introduction: Tourism is a vital driver of economic growth, cultural exchange, and regional development. Proper planning and strategic placement of tourist agglomerations – areas concentrated with attractions, services, and facilities catering to visitors – can significantly enhance the appeal of a region while ensuring sustainable development. However, determining the optimal locations for such agglomerations poses complex challenges due to the need to balance multiple criteria, including accessibility, resource availability, environmental impact, and economic feasibility. The rapid advancement of data analytics, Geographic Information Systems (GIS), and optimization algorithms offers new opportunities to address these challenges. Algorithmic approaches provide a systematic framework for analyzing large volumes of spatial and non-spatial data, identifying patterns, and generating data-driven solutions that can guide decision-making. By integrating techniques such as clustering, multi-criteria decision-making, and optimization models, regions can achieve more efficient and sustainable outcomes in the placement of tourist agglomerations. This paper explores algorithmic methodologies to optimize the placement of tourist hubs in a given region. The proposed approach combines GIS-based analysis to evaluate geographic and environmental factors with advanced 100 THEORETICAL ASPECTS IN THE FORMATION OF PEDAGOGICAL SCIENCES International scientific-online conference algorithms to optimize resource allocation and visitor accessibility. Furthermore, the study emphasizes the importance of sustainability and stakeholder engagement in shaping tourism development strategies. The following sections discuss the theoretical framework, methodology, case studies, and results, highlighting the potential of algorithmic approaches to transform regional tourism planning. The findings aim to serve as a valuable resource for policymakers, urban planners, and tourism developers seeking to enhance the economic and social impact of tourism while minimizing adverse effects on the environment. In an algorithmic approach to optimal placement of Tourism agglomerations, we studied the classification of applications, assessment tools and approaches of several mathematical formulas and optimization models in a generalized state. In order to optimally place tourism agglomerations in the region, several mathematical formulas and optimization models can be applied in an algorithmic approach. Through these formulas, it is possible to calculate the optimal location of tourism resources and the effective distribution of infrastructure. Applied to forecast tourist flows, taking into account the distance between tourism agglomerations and the population density. "Gravitational model" this model works similarly to the law of gravity. 𝑃 × 𝑃 𝑖 𝑗 𝑇 = 𝑖𝑗 𝑑2 𝑖𝑗 Here is the influx of tourists between places Tij - I and J; population or tourist potential of places Pi , Pj - I and j; distance between places dij - I and J. This model can be used to calculate the distance between major tourist centers such as Shahrisabz and Qarshi and the gravity of tourists. With this, it is possible to determine in which direction tourists move the most. Lagrange multipliers are used to solve constraint optimization problems. If natural resources, infrastructure and economic resources are limited when deploying tourism agglomerations, optimal placement is determined through Lagrange multipliers 𝐿(𝑥 ,𝑥 𝜕) = 𝑓(𝑥 𝑥 ) + 𝜕(𝑔(𝑥 𝑥 ) − 𝑐) 1 2 1 2 1 2 Where Z is the total cost or distance (which must be minimized); Hello is the flow of tourists at point I; dij is the distance between point I and point j; xij is 1 If place I is connected to service place j, otherwise 0. It can be used to minimize 101 THEORETICAL ASPECTS IN THE FORMATION OF PEDAGOGICAL SCIENCES International scientific-online conference the distance between tourist service zones (hotels, restaurants and recreation zones). This reduces travel costs and increases tourist comfort. This is also known as the distance minimization model (p-median model). It is an optimization model used in operational research and logistics, with the main objective of positioning service areas in a way that minimizes distances associated with customers or users. This model is used to optimize the placement of service tourism centers, especially