000			03073nam a22002057a 4500
005			20250115171310.0
008			250115b |||||||| |||| 00| 0 eng d
020			_a9783031512407
082			_a658.7 _bIVA
100			_aIvanov, Dmitry
245			_aIntroduction to supply chain analytics: _bwith examples in anylogic and anylogistix software
260			_bSpringer _aCham _c2024
300			_axii, 167 p
365			_aEUR _b99.99
490			_aClassroom Companion
500			_aTable of content: Analytics and Model-Based Decision-Making Support Dmitry Ivanov Pages 1-20 Demand Forecasting, Production Planning, and Inventory Control Dmitry Ivanov Pages 21-47 Discrete Event Simulation of Manufacturing Processes and Inventory Control Dmitry Ivanov Pages 49-102 Facility Location Planning and Network Optimization Dmitry Ivanov Pages 103-131 Supply Chain Risk and Resilience Analytics Dmitry Ivanov Pages 133-164 Back Matter Pages 165-167 [https://link.springer.com/book/10.1007/978-3-031-51241-4]
520			_aThe book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook “Global Supply Chain and Operations Management”, it addresses the topics of supply chain analytics in more depth. The book describes descriptive, predictive, and prescriptive supply chain analytics explaining methodologies, illustrating method applications with the use of training exercises, and providing numerous examples in AnyLogic and anyLogistix software. Throughout the book, numerous practical examples and short case studies are given to illustrate theoretical concepts. Along with AnyLogic and anyLogistix model development guidelines and examples, the book has two other distinct features. First, it reviews and explains novel frameworks and concepts related to data-driven decision-making and digital twins. Second, it shows how to use analytics to improve supply chain resilience. Without relying heavily on mathematical derivations, the book offers a structured presentation and explanation of major supply chain analytics techniques and principles in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering backgrounds. Graduate/Ph.D. students and supply chain professionals alike would benefit from a structured and didactically-oriented concise presentation of the concepts, principles, and methods of supply chain analytics. Providing graduate students and supply chain managers with working knowledge of basic and advanced supply chain analytics, this book contributes to improving knowledge-awareness of decision-making in increasingly data-driven and digital environments. The book is supplemented by a companion website offering interactive exercises with the use of AnyLogic and anyLogistix software as well as Spreadsheet Modeling. (https://link.springer.com/book/10.1007/978-3-031-51241-4)
650			_aSupply chain management
942			_cBK _2ddc
999			_c8553 _d8553