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Inventory Optimization : Models and Simulations / Nicolas Vandeput.

By: Contributor(s): Material type: TextTextPublisher: Berlin ; Boston : De Gruyter, [2020]Copyright date: ©2020Description: 1 online resource (XXVI, 292 p.)Content type:
Media type:
Carrier type:
ISBN:
  • 9783110673913
  • 9783110673999
  • 9783110673944
Subject(s): Other classification:
  • online - DeGruyter
Online resources:
Contents:
Frontmatter -- Acknowledgments -- About the Author -- Foreword -- Contents -- Introduction -- Part I: Deterministic Supply Chains -- 1 Inventory Policies -- 2 How Much Should I Order? -- 3 When Should I Order? -- Part II: Stochastic Supply Chains -- 4 Safety Stocks -- 5 Inventory Policies -- 6 Stochastic Lead Times -- Part III: Advanced Stochastic Models -- 7 Fill Rate -- 8 Cost and Service Level Optimization -- 9 Beyond Normality -- 10 Multi-Echelon Inventory Optimization -- Part IV: Discrete Inventory Optimization -- 11 Newsvendor -- 12 Discrete Probabilistic Demand -- 13 Simulation Optimization -- Now It Is Your Turn! -- A Python -- B Proofs -- Bibliography -- Glossary -- List of Symbols -- Index
Summary: In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple—yet powerful—framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter. Check out the webinar on the book!The author and his guests talk about how to take inventory optimization to the next level: https://www.youtube.com/watch?v=565fDQMJEEg&t=8s
Holdings
Item type Current library Call number URL Status Notes Barcode
eBook eBook Biblioteca "Angelicum" Pont. Univ. S.Tommaso d'Aquino Nuvola online online - DeGruyter (Browse shelf(Opens below)) Online access Not for loan (Accesso limitato) Accesso per gli utenti autorizzati / Access for authorized users (dgr)9783110673944

Frontmatter -- Acknowledgments -- About the Author -- Foreword -- Contents -- Introduction -- Part I: Deterministic Supply Chains -- 1 Inventory Policies -- 2 How Much Should I Order? -- 3 When Should I Order? -- Part II: Stochastic Supply Chains -- 4 Safety Stocks -- 5 Inventory Policies -- 6 Stochastic Lead Times -- Part III: Advanced Stochastic Models -- 7 Fill Rate -- 8 Cost and Service Level Optimization -- 9 Beyond Normality -- 10 Multi-Echelon Inventory Optimization -- Part IV: Discrete Inventory Optimization -- 11 Newsvendor -- 12 Discrete Probabilistic Demand -- 13 Simulation Optimization -- Now It Is Your Turn! -- A Python -- B Proofs -- Bibliography -- Glossary -- List of Symbols -- Index

restricted access online access with authorization star

http://purl.org/coar/access_right/c_16ec

In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple—yet powerful—framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter. Check out the webinar on the book!The author and his guests talk about how to take inventory optimization to the next level: https://www.youtube.com/watch?v=565fDQMJEEg&t=8s

Mode of access: Internet via World Wide Web.

In English.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021)