Author(s)

DingYi Ma^1*, KeYin Zhu², Lei Zang¹

Affiliation(s)

¹School of Materials Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan, China.

²School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, Henan, China.

Corresponding Author

DingYi Ma

ABSTRACT

Rapid tourism growth has boosted local economies but also posed environmental and social challenges, highlighting the need for sustainable management. This study presents a hybrid optimization framework that integrates Genetic Algorithm with Particle Swarm Optimization (GA-PSO) with a Coupling Coordination Degree (CCD) mechanism to balance social, economic, and environmental subsystems. The model targets maximization of employment, tourism revenue, and glacier stability under statistical and coordination constraints. Regression analysis and the entropy weight–TOPSIS method were applied to quantify subsystem interactions. Results show that GA-PSO outperforms single GA and PSO, achieving an optimal coordination degree of 0.6254. Employment, tourism revenue (USD 147 million), and environmental sustainability all showed notable improvements. This research extends the use of hybrid evolutionary algorithms in sustainable tourism and provides quantitative support for policymakers seeking to balance economic growth, social well-being, and ecological resilience.

KEYWORDS

Sustainable tourism; Multi-objective optimization; GA-PSO; Coupling coordination degree

CITE THIS PAPER

DingYi Ma, KeYin Zhu, Lei Zang. A hybrid GA-PSO and coupling coordination framework for multi-objective optimization in sustainable tourism systems. World Journal of Economics and Business Research. 2025, 3(4): 1-7. DOI: https://doi.org/10.61784/wjebr3059.

REFERENCES

[1] Caric H. Challenges and prospects of valuation–cruise ship pollution case. Journal of cleaner production. 2016, 111: 487-498. 

[2] Klein R A. Responsible cruise tourism: Issues of cruise tourism and sustainability. Journal of Hospitality and Tourism Management. 2011, 18(1): 107-116.

[3] Hu X, Dong C, Wang Y. Coupled and coordinated analysis of urban green development and ecological civilization construction in the Yangtze River Delta region. Sustainability. 2023, 15(7): 5955.

[4] Yin Z, Tang Y, Liu H, et al. Coupling coordination relationship between tourism economy-social welfare-ecological environment: Empirical analysis of Western Area, China. Ecological Indicators. 2023, 155: 110938.

[5] Tang C, Zeng R, Han Y. Coupling coordination evaluation of economic development, ecological environment, and the tourism industry in ski resorts. Journal of Cleaner Production. 2023, 426: 139076.

[6] Luo Z, Xu A, Gao S. Research on the coupling coordination relationship between tourism carrying capacity and the high-speed railway network: a case study in China. IEEE Access. 2023, 11: 20426-20444.

[7] Gautam V, Bhalla S. Exploring the relationships among tourism involvement, residents' empowerment, quality of life and their support for sustainable tourism development. Journal of Cleaner Production. 2024, 434: 139770.

[8] Hafsi H, Gharsellaoui H, Bouamama S. Genetically-modified multi-objective particle swarm optimization approach for high-performance computing workflow scheduling. Applied soft computing. 2022, 122: 108791.

[9] Arbolino R, Boffardi R, De Simone L, et al. Multi-objective optimization technique: A novel approach in tourism sustainability planning. Journal of Environmental Management. 2021, 285: 112016.

[10] Su F, Duan C, Wang R. Optimization model and algorithm design for rural leisure tourism passenger flow scheduling. Ieee Access. 2020, 8: 125295-125305.

[11] Tan Q. Research on sustainable carrying capacity of urban tourism environment based on multi objective optimization algorithm. Results in Engineering. 2023, 19: 101344.

[12] Shi T. Coupling coordination degree and spatial network effect of ecological protection and high-quality economic development in the Yellow River Basin. German Economic Review. 2020, 3: 25-34.