Название: Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management
Автор: Dinesh K. Sharma, Madhu Jain
Издательство: Springer
Год: 2022
Страниц: 293
Язык: английский
Формат: pdf (true), epub
Размер: 41.0 MB

This book considers new analytics and Artificial Intelligence (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.

Intelligent computing can be used in supply chain management to tackle huge volumes of data, understand relationships of demand vs supply, optimize the earnings before interest, taxes, depreciation, and amortization for better decision-making in an organization as an integrated end to end supply chain. Artificial intelligence (AI)-driven tools can provide valuable insights for the inventory, logistics, warehouse efficiency, on time delivery, forecasting of supply and demand. AI-based solution-agnostic assessment and strategy will support the companies for better alignment and inventory control, and capabilities to create a strategic intelligent road map for the supply chain and logistics.

This book contains various inventory and supply chain models to tackle logistics and optimization problems. Recent developments in the areas of nature-inspired optimization and AI approaches to manage an end to end inventory and supply chains for implementation and system integration have been presented. The models and performance analysis presented facilitated valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. This book offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal decision.

This book consists of 15 chapters that bring interesting aspects of modeling and applications of artificial intelligent computing and optimization techniques in inventory and supply chain management. The subject presented in the book will be beneficial for academicians, researchers and practitioners to get ideas about recent advances in the modeling and data analytics for the optimal decision of inventory, logistics and supply chain. In different chapters of the book statistical, optimization and AI techniques for the stochastic inventory control and supply chain management are presented.