OICC Press International Journal of Energy and Environmental Engineering 2251-6832 15 02 (June 2024) 2024 06 30 The STMO Model for Balancing Growth and Conservation in Juneau, Alaska 10.57647/ijeee.2024.1502.10 EN Jinyu Wang School of Computer Engineering, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China Zeren Yu School of International Business, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China Jing Li School of Computer Engineering, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China Yunpeng Shang Engineering Institute, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China Hongjun Lin School of Computer Engineering, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China Journal Article 2024 06 30 Juneau, Alaska, faces rapidly increasing visitor numbers, generating substantial economic gains while intensifying environmental pressures and social tensions. To address these challenges, this study develops a dynamic multi-objective optimization model that jointly considers economic revenue, ecological degradation, and social carrying capacity. The model integrates feedback loops and reinvestment strategies, demonstrating how visitor caps, tax policies, and targeted expenditures influence long-term system outcomes. Sensitivity analysis and simulation results identify the parameters most critical to sustainable tourism management, including infrastructure efficiency, environmental mitigation rates, and community development investment. Although Juneau serves as the case study, the framework is generalizable and can be adapted to other overtourism destinations by calibrating site-specific constraints and priorities. The findings highlight actionable pathways for balancing growth and conservation, while offering methodological and policy insights that extend to the field of overtourism research globally. Although the literature on overtourism has examined economic, social, and environmental impacts, it lacks a dynamic, multi-objective framework capable of capturing feedback loops and long-term trade-offs. Existing models are largely static or single-dimensional, leaving destinations without tools to understand how economic, social, and environmental outcomes interact over time. This study fills that gap by introducing a dynamic optimization model integrating revenue generation, ecological degradation, and social carrying capacity, offering a comprehensive structure for long-term sustainable tourism planning.