This book investigates the role of optimization methods and data science techniques in improving both internal and external logistics operations, with particular emphasis on last-mile logistics. It explores mathematical models, heuristics, and data-driven approaches for enhancing routing, inventory management, resource allocation, and operational planning under real-world constraints. Special attention is given to the civil applications of emerging technologies, including artificial intelligence, IoT, AGV and UAV, as key enablers of more efficient and sustainable logistics processes. The book also examines the environmental and organizational challenges facing contemporary logistics, with the objective of reducing emissions, congestion, energy consumption, and operational inefficiencies across both urban and rural contexts. By integrating methodological perspectives with practical case studies, it provides a rigorous framework for the design of smarter and more sustainable systems.

This book investigates the role of optimization methods and data science techniques in improving both internal and external logistics operations, with particular emphasis on last-mile logistics. It explores mathematical models, heuristics, and data-driven approaches for enhancing routing, inventory management, resource allocation, and operational planning under real-world constraints. Special attention is given to the civil applications of emerging technologies, including artificial intelligence, IoT, AGV and UAV, as key enablers of more efficient and sustainable logistics processes. The book also examines the environmental and organizational challenges facing contemporary logistics, with the objective of reducing emissions, congestion, energy consumption, and operational inefficiencies across both urban and rural contexts. By integrating methodological perspectives with practical case studies, it provides a rigorous framework for the design of smarter and more sustainable systems.