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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.
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