Tourism Development Study of Juno ICSS Model Based on Multi-Objective Genetic Algorithm NSGA-II

Abstract

This paper focuses on sustainable tourism and constructs an ICSS model based on the multi-objective genetic algorithm NSGA-II for Juneau, aiming at solving the multi-objective optimization problem and determining the optimal number of tourists per day, which can provide a basis for policy formulation. The objective function of the model takes into account the total local income, the implicit cost of environmental protection policy and the satisfaction of residents, and sets the constraints of the number of tourists, implicit cost and the satisfaction of residents at the same time. The relationship between the variables is determined by establishing sub-models of income, hidden costs and residents' satisfaction. After parameterization and simulation, it is concluded that the sustainable tourism evaluation index Z is maximized when the number of daily tourists in Juneau reaches 9,500. The model can be migrated to other cities affected by over-tourism, such as Honolulu, where the optimal number of visitors is 13,200 after re-fitting the parameters. In addition, considering the situation of multiple attractions in the city, the SST model is improved to optimize the evaluation indexes, balance the number of tourists in the attractions, and improve the utilization rate of resources, which provides a reference for tourism planning.