مقاله انگلیسی بهینه‌سازی مکان‌یابی صنایع با هوش مصنوعی بر اساس توسعه پایدار

Applying artificial intelligence in the location of factories and service institutions, taking into account the goals of sustainable development

Abstract

This article develops the fact that artificial intelligence (AI) is essentially a transformative practice in sustainable development, with respect to strategic placements of factories and service institutions. This paper analyzes the role that AI would play in optimally influencing the decision-making process of sustainable facility placement. The paper will cover an extensive analysis ranging from a review of the literature to an exploration of theory, assessment of methodology, and synthesized findings from case studies. The purpose of the paper is to review the emerging AI technologies of machine learning, geographic information systems (GIS), and predictive analytics in light of solving complex sustainability problems under economic, environmental, and social dimensions. These results will underline the role AI has to play in realizing efficiency, reduced environmental impacts, and serving equitable access to services, importantly, for their large contributions to the attainment of the SDGs. Key concerns such as data privacy, ethical considerations, and cross-disciplinary collaboration have been reported as arising. Finally, the article leaves the reader with actionable recommendations that would maximize AI’s contribution to sustainable development by underlining the essential role of interdisciplinary collaboration, robust governance frameworks, and stake elements of stakeholder engagement, besides a focus on continuous innovation. This further adds to increased discourse in relation to leveraging AI for sustainable development, thereby giving insights in reference to opportunities and challenges around integrating technology and sustainability principles within urban planning and industrial practice.

Keywords: Artificial Intelligence, Sustainable Development, Facility Placement, Machine Learning, Geographic Information Systems, Predictive Analytics, Sustainability Challenges, Sustainable Development Goals, Urban Planning, Ethical Considerations.