Multi-Objective Optimization Study on Tourism Destination Sustainable Development Based On NSGA-II

Abstract

Against the backdrop of the booming global tourism industry, how to crack the development dilemma of tourism destinations between economic benefits, environmental protection and residents' well-being has become a key issue to be solved. In this study, a multi-objective dynamic optimization model based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) is constructed for the city of Akureyri, Iceland, as a typical case, in response to the composite challenges of glacier recession, out-migration of residents and financial pressure triggered by the surge of its cruise tourism. By integrating 12 key indicators in the three dimensions of tourism income, carbon emission, and residents' satisfaction from 2007 to 2022, and combining the hierarchical analysis method to determine the weighting system of economy (α=0.5), environment (β=0.3), and society (γ=0.2), the model reveals that the number of tourists and the per capita consumption price are the key sensitivity parameters, where a change in the number of tourists by ±10% will lead to fluctuations in income ± 15.8% and carbon emission change ±7.3%. The model validation shows that the dynamic regulation of attraction diversion strategy and seasonal price adjustment mechanism provides a quantifiable decision-making framework for global tourist cities to solve the triangle paradox of “development-ecology-livelihood”.