Maximizing reader insights into the challenges facing maritime supply chains and container port logistics service providers in Asia, this book highlights their innovative responses to these challenges through real-world case studies. With a focus on mathematical modeling, simulation and heuristics approaches, this book provides academics, engineers, container terminal operators, students in logistics and supply chain management with the latest approaches that can be used to address the planning and scheduling problem in large container terminal yards. This book can be used on a self-contained basis as teaching cases in an undergraduate or specialist class setting, or on techniques applied to maritime container operations for port operations.

This book reveals the secrets of Yamato Transport's success in maintaining and extending its leadership in Japan's domestic parcel delivery market. It presents six cases that illustrate how Yamato's flagship service, TA-Q-BIN, has evolved since the 1970s to the benefit of consumers, particularly urban dwellers, and how TA-Q-BIN has become an integral part of Japanese daily life. Each of the six unique cases serves as an independent teaching case for undergraduate and graduate students, describing the particular service design, operations management, innovation, supplier management, and social responsibility within the context of an Asian last-mile logistics service provider. The book also includes insightful presentations of the challenges facing supply chain and logistics service providers in Asia, and their innovative responses to these challenges using real-world cases. Besides featuring interviews with Yamato's key stakeholders and their strategic clients, Japan-based and other Asia-Pacific Yamato operational centers make up the field method included in this book, while secondary data is drawn from trade and academic domains. Some of the cases are written in a didactic fashion, with suitable stopping points for students to pause and deliberate over the managerial issues confronting the decisions that Yamato makes during the course of its business and operational strategies. The results are particularly useful to readers interested in how operations and logistics decision-making are practiced in a homogeneous Asian context and in an urban environment. This book is essential reading for undergraduate and MBA students, as well as practitioners in industry.

Maximizing reader insights into the challenges facing maritime supply chains and container port logistics service providers in Asia, this book highlights their innovative responses to these challenges through real-world case studies. With a focus on mathematical modeling, simulation and heuristics approaches, this book provides academics, engineers, container terminal operators, students in logistics and supply chain management with the latest approaches that can be used to address the planning and scheduling problem in large container terminal yards. This book can be used on a self-contained basis as teaching cases in an undergraduate or specialist class setting, or on techniques applied to maritime container operations for port operations.

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.