## 6 Conclusions  
This study presents a novel multi-objective optimization model for BTS site selection in telecommunication networks, integrating sustainability, cost-effectiveness, and service quality as critical objectives. By addressing key challenges in telecom network planning and green infrastructure development, the model contributes significantly to achieving optimal solutions that balance operational efficiency and environmental stewardship. The proposed hub location framework not only ensures robust coverage in dynamic demand environments but also incorporates environmental disruptions to enhance network resilience. Its adaptability across diverse scenarios, from densely populated urban areas to remote rural regions, underscores its potential for equitable access to telecommunication services.  
Key findings highlight the superior performance of the NSGA-II algorithm in medium-sized scenarios, emphasizing its utility in solving complex multi-objective problems efficiently. The incorporation of real-world constraints, such as capacity limitations and environmental factors, further validates the model's applicability in practical settings. In addition to the quantitative results, the graphical representations provided throughout the paper illustrate the model's robustness and applicability. These visual aids serve to bridge theoretical constructs with practical implications, enabling a deeper understanding of the findings.  
The inclusion of real-time optimization approaches, coupled with the analysis of varying demand scenarios, underscores the robustness of the proposed framework. These enhancements provide a pathway for more dynamic and responsive telecommunication network solutions, ensuring optimal decision-making under evolving conditions.  
This research advances the field of sustainable telecommunication network planning by providing a scalable and flexible solution. Future studies could expand the model'sscope by integrating real-time traffic data and advanced machine learning algorithms to enhance predictive accuracy and adaptability. Additionally, exploring the inclusion of more nuanced environmental parameters, such as energy consumption metrics and carbon footprints, could further align the model with industry sustainability goals. In summary, this study lays a solid foundation for next-generation telecommunication network planning, offering a versatile and practical tool for operators and policymakers to address the pressing demands of modern infrastructure while maintaining a commitment to environmental responsibility.  
Conceptualization, S.B. and M.K. ([PERSON]); methodology, S.B.; software, M.K. ([PERSON]); validation, S.B., M.K. ([PERSON]) and R.E.; formal analysis, S.B.; investigation, S.B.; resources, M.K. ([PERSON]); data curation, M.K. ([PERSON]); writing--original draft preparation, S.B.; writing--review and editing, M.K. ([PERSON]); visualization, M.K. ([PERSON]); supervision, M.K. ([PERSON]); project administration, M.K. ([PERSON]); funding acquisition, R.E. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The data presented in this study are available on request from the corresponding author. Due to privacy and ethical restrictions, the data are not publicly accessible.  
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.