Smart Logistics: Designing and Implementing AI-Driven Decision Support Systems

This chapter explores the transformative impact of these systems on logistics, highlighting their role in optimizing operations, enhancing decision-making, and improving overall efficiency. The chapter also examines implementation strategies, including the integration of machine learning models, real-time data processing, and predictive analytics, to facilitate informed decision-making across various logistics functions such as inventory management, route optimization, and demand forecasting. Case studies of leading logistics companies are presented to illustrate successful applications and the tangible benefits achieved. Additionally, the chapter addresses challenges related to data security, scalability, and the need for continuous system updates to adapt to changing market conditions. By providing a comprehensive overview of the design and implementation processes, this chapter aims to guide logistics professionals and researchers in leveraging AI-driven DSS to create smarter, more responsive logistics networks..