This book explores how optimization and data science significantly impact the operations of supply chain and logistics and investigates them extensively for additional benefits. It demonstrates the concept and implementation of data science methods, advanced analytics, optimization, metaheuristics, and machine learning algorithms developed over the years for critical decision-making in warehousing, inventory, and transportation in supply chain management that facilitates the optimization of supply chain and logistics operations. It covers the following topics with an emphasis on their applications in areas like supply chain coordination, pricing and revenue management, warehousing, reverse logistics, facility location and supply chain network design, transportation and routing. The book is a great resource for senior undergraduate students intending to get themselves acquainted with interesting future trends in the topic, postgraduate students curious to augment their knowledge in the detailed theory and applications of the topic, PhD and postdoctoral students who want to focus in-depth on the stimulating research areas on these issues, and practitioners from industry who wish to explore fruitful applications and their future trends in supply chain and logistics.