The rapid urbanization has intensified the need for environmentally conscious supply chains (SCs) and logistics strategies that leverage cutting-edge technologies and data analytics. This chapter provides a comprehensive review of the literature on intelligent decision-making methods and artificial intelligence (AI) applications designed to address complex logistics and SC challenges in smart cities. The review methodology follows a systematic approach, utilizing databases such as Scopus, Web of Science, IEEE Xplore, and Science Direct to examine peer-reviewed publications from 2007 to 2024. The analysis prioritizes high-impact journals, conference proceedings, relevance to research objectives, and citation metrics, ensuring a thorough exploration of key trends and developments. Focusing on urban logistics, this review explores how AI-driven approaches are transforming the management of goods and services flows in rapidly growing urban environments. It highlights the transformative potential of technologies such as Internet of Things (IoT), blockchain, autonomous vehicles, and digital twins, integrated with optimization algorithms and AI techniques like machine learning and multi-agent systems. These technologies enable seamless monitoring, optimization, and automation of logistics workflows, improving efficiency, resilience, and sustainability across domains such as transportation, warehousing, waste management, and circular economy initiatives. Policy frameworks, public-private collaboration, and community involvement are identified as crucial for advancing intelligent, sustainable logistics practices. Challenges like data privacy, infrastructure requirements, and stakeholder coordination are also discussed, offering insights for researchers, practitioners, and policymakers aiming to develop and implement environmentally responsible SC solutions in urban areas.