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Author: Dinesh K. Sharma
Publisher:
ISBN: 9789811963384
Category :
Languages : en
Pages : 0
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Book Description
This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included. The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics. .
Author: Dinesh K. Sharma
Publisher:
ISBN: 9789811963384
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included. The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics. .
Author: Dinesh K. Sharma
Publisher: Springer Nature
ISBN: 9811963371
Category : Business & Economics
Languages : en
Pages : 293
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Book Description
This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included.The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics.
Author: Allam Hamdan
Publisher: Springer Nature
ISBN: 3030627969
Category : Technology & Engineering
Languages : en
Pages : 483
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Book Description
This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy.
Author: Katrin Bergener
Publisher: Springer
ISBN: 3030062341
Category : Computers
Languages : en
Pages : 535
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Book Description
Structuring, or, as it is referred to in the title of this book, the art of structuring, is one of the core elements in the discipline of Information Systems. While the world is becoming increasingly complex, and a growing number of disciplines are evolving to help make it a better place, structure is what is needed in order to understand and combine the various perspectives and approaches involved. Structure is the essential component that allows us to bridge the gaps between these different worlds, and offers a medium for communication and exchange. The contributions in this book build these bridges, which are vital in order to communicate between different worlds of thought and methodology – be it between Information Systems (IS) research and practice, or between IS research and other research disciplines. They describe how structuring can be and should be done so as to foster communication and collaboration. The topics covered reflect various layers of structure that can serve as bridges: models, processes, data, organizations, and technologies. In turn, these aspects are complemented by visionary outlooks on how structure influences the field.
Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030697444
Category : Technology & Engineering
Languages : en
Pages : 594
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Book Description
This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.
Author: R. Kanthavel
Publisher: John Wiley & Sons
ISBN: 1119821789
Category : Computers
Languages : en
Pages : 388
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Book Description
ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.
Author: Chan, Hing Kai
Publisher: IGI Global
ISBN: 1522509577
Category : Business & Economics
Languages : en
Pages : 319
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Book Description
Technological advancements in recent years have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Supply Chain Management in the Big Data Era is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes. Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations.
Author: Thomas Y. Choi
Publisher:
ISBN: 9780190066734
Category : Business logistics
Languages : en
Pages :
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Book Description
This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online.
Author: Nita H. Shah
Publisher: Springer Nature
ISBN: 9811396981
Category : Business & Economics
Languages : en
Pages : 466
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Book Description
This book discusses inventory models for determining optimal ordering policies using various optimization techniques, genetic algorithms, and data mining concepts. It also provides sensitivity analyses for the models’ robustness. It presents a collection of mathematical models that deal with real industry scenarios. All mathematical model solutions are provided with the help of various optimization techniques to determine optimal ordering policy. The book offers a range of perspectives on the implementation of optimization techniques, inflation, trade credit financing, fuzzy systems, human error, learning in production, inspection, green supply chains, closed supply chains, reworks, game theory approaches, genetic algorithms, and data mining, as well as research on big data applications for inventory management and control. Starting from deterministic inventory models, the book moves towards advanced inventory models. The content is divided into eight major sections: inventory control and management – inventory models with trade credit financing for imperfect quality items; environmental impact on ordering policies; impact of learning on the supply chain models; EOQ models considering warehousing; optimal ordering policies with data mining and PSO techniques; supply chain models in fuzzy environments; optimal production models for multi-items and multi-retailers; and a marketing model to understand buying behaviour. Given its scope, the book offers a valuable resource for practitioners, instructors, students and researchers alike. It also offers essential insights to help retailers/managers improve business functions and make more accurate and realistic decisions.
Author: Nada R. Sanders
Publisher: Pearson Education
ISBN: 0133762823
Category : Business & Economics
Languages : en
Pages : 273
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Book Description
Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.
