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Einführung in Supply Chain Analytics: Mit Beispielen in AnyLogic und anyLogisti
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Standort: Fairfield, Ohio, USA
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eBay-Artikelnr.:388503406568
Artikelmerkmale
- Artikelzustand
- ISBN-13
- 9783031512407
- Type
- NA
- Publication Name
- NA
- ISBN
- 9783031512407
Über dieses Produkt
Product Identifiers
Publisher
Springer
ISBN-10
3031512405
ISBN-13
9783031512407
eBay Product ID (ePID)
13064172244
Product Key Features
Book Title
Introduction to Supply Chain Analytics : with Examples in Anylogic and Anylogistix Software
Number of Pages
Xii, 167 Pages
Language
English
Topic
Probability & Statistics / General, Economics / General, Production & Operations Management, Databases / General
Publication Year
2024
Illustrator
Yes
Genre
Mathematics, Computers, Business & Economics
Book Series
Classroom Companion: Business Ser.
Format
Hardcover
Dimensions
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Number of Volumes
1 vol.
Dewey Decimal
658.70285
Table Of Content
Analytics and model-based decision-making support.- Demand Forecasting, Production Planning and Inventory Control.- Discrete-Event Simulation of manufacturing processes and inventory control.- Facility location planning and network optimization.- Supply chain risk and resilience analytics.
Synopsis
The 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.
LC Classification Number
HD38.5
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