Research on Cooperative Resource Management of Rural Tourism Attractions Combining Multi-objective Optimization and Data Mining
Publicado en línea: 21 mar 2025
Recibido: 17 nov 2024
Aceptado: 17 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0583
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© 2025 Xiaolu Xu, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Tourism development depends on the survival of the resource environment is a constantly changing and evolution of the composite system, tourism resources and environment of the advantages and disadvantages of determining the sustainable development and competitiveness of tourist destinations. This paper takes the resource synergistic management of rural tourist attractions as the research object, and realizes the sustainable synergistic development of economy, society and ecology through the multi-objective optimization of its resource and environmental carrying capacity. The system dynamics model is constructed to simulate and predict the resource and environmental carrying capacity of rural tourist attractions, and the NSGA-Ⅱ algorithm is used to realize the multi-objective optimization of resource and environmental carrying capacity based on the predicted value. Based on the data of tourism scale and tourism income of A rural tourism scenic spot from 2014 to 2023, the system dynamics simulation of its resource and environmental carrying potential was carried out, and its predicted data in 2030 under the continuation of the status quo was obtained. Relative to the actual value in 2023, the predicted value of the indicators of tourist attractions in Rural A only decreases from 1.47×106m³ to 1.43×106m³ in terms of water supply capacity, and all other indicators are significantly improved, indicating that Rural A will realize a larger development of its own carrying capacity while sacrificing a small amount of water supply capacity. Furthermore, this paper simulates and solves the optimization model using the NSGA-II algorithm, which provides a reference for the decision maker to choose a scheme by searching for the optimal solution set.