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Data analytics and artificial intell...

Sharma, Dinesh K.

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Data analytics and artificial intelligence for inventory and supply chain management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data analytics and artificial intelligence for inventory and supply chain management/ edited by Dinesh K. Sharma, Madhu Jain.
其他作者:	Sharma, Dinesh K.
出版者:	Singapore :Springer Nature Singapore : : 2022.,
面頁冊數:	xx, 284 p. :ill. (chiefly color), digital ;24 cm.
內容註:	Markov Decision Processes of a Two-tier Supply Chain Inventory System -- Nature-Inspired Optimization for Inventory Models with Imperfect Production -- A Multi-Objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- Artificial Intelligence Computing and Nature Inspired Optimization Techniques for Effective Supply Chain Management -- An EPQ Model for Imperfect Production System with Deteriorating Items, Price Dependent Demand, Rework and Lead Time under Markdown Policy -- Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- Inventory Model for Growing Items and Its Waste Management -- Pavement Cracks Inventory Survey with Machine Deep Learning Models -- Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model -- Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment.
Contained By:	Springer Nature eBook
標題:	Business logistics - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-19-6337-7
ISBN:	9789811963377

Data analytics and artificial intelligence for inventory and supply chain management
Data analytics and artificial intelligence for inventory and supply chain management[electronic resource] /edited by Dinesh K. Sharma, Madhu Jain. - Singapore :Springer Nature Singapore :2022. - xx, 284 p. :ill. (chiefly color), digital ;24 cm. - Inventory optimization,2730-9355. - Inventory optimization..

Markov Decision Processes of a Two-tier Supply Chain Inventory System -- Nature-Inspired Optimization for Inventory Models with Imperfect Production -- A Multi-Objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning -- Artificial Intelligence Computing and Nature Inspired Optimization Techniques for Effective Supply Chain Management -- An EPQ Model for Imperfect Production System with Deteriorating Items, Price Dependent Demand, Rework and Lead Time under Markdown Policy -- Retrial Inventory-Queueing Model with Inspection Processes and Imperfect Production -- Inventory Model for Growing Items and Its Waste Management -- Pavement Cracks Inventory Survey with Machine Deep Learning Models -- Decarbonisation Through Production of Rhino Bricks From the Waste Plastics: EPQ Model -- Cost Analysis of Supply Chain Model for Deteriorating Inventory Items with Shortages in Fuzzy Environment.

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.

ISBN: 9789811963377

Standard No.: 10.1007/978-981-19-6337-7doiSubjects--Topical Terms:

731545
Business logistics
--Data processing.

LC Class. No.: HD38.5

Dewey Class. No.: 658.70285

Data analytics and artificial intelligence for inventory and supply chain management
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520 $a 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.
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