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Problems & Solutions in Inventory Management / by Dinesh Shenoy, Roberto Rosas.

By: Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018Description: 1 online resource (XIII, 283 pages 49 illustrations, 6 illustrations in color.)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319656960
Subject(s): Additional physical formats: Print version:: Problems & solutions in inventory management; Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 658.5 S546p 22
Contents:
Part - I : Basics of Inventory Management -- Chapter 1. Introduction to Inventory Management -- Chapter 2. Inventory Control Systems - Design Factors -- Part - II: Single-Item Inventory Models -- Chapter 3. Deterministic Inventory Models -- Chapter 4. Dynamic Inventory Control Models -- Chapter 5. Lot-sizing Heuristics -- Chapter 6. Stochastic Inventory Models -- Part - III: Multi-item Inventory Models -- Chapter 7. Multi-item Inventory Models Subject to Constraints -- Chapter 8. Selective Inventory Control Models -- Part - IV: Advanced Inventory Models -- Chapter 9. Inventory Models for Perishable Items and Style Goods -- Chapter 10- Inventory Models for Maintenance and Repairable Items -- Chapter 11. Multiechelon Inventory Models.
Summary: This book presents a compilation of over 200 numerical problems and solutions that students can use to learn, practice and master the Inventory Control and Management concepts. Intended as a companion to any of the standard textbooks in Inventory Control and Management and written in simple language, it illustrates very clearly the steps students need to follow in order to solve a given problem. It also explains which solution methodologies can be used under which circumstances. Offering an ideal one-stop resource for mid-level engineering and business students who have taken Inventory Management or a related subject as an elective, this book is the only one students will ever need to prepare and gain confidence for their examinations in this subject.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Books Books Chittagong University Library 658.5 S546p (Browse shelf(Opens below)) c-1 Available 329977
Books Books Chittagong University Library 658.5 S546p (Browse shelf(Opens below)) C-2 Available 329978
Books Books Chittagong University Library 658.5 S546p (Browse shelf(Opens below)) C-3 Available 329979

Part - I : Basics of Inventory Management -- Chapter 1. Introduction to Inventory Management -- Chapter 2. Inventory Control Systems - Design Factors -- Part - II: Single-Item Inventory Models -- Chapter 3. Deterministic Inventory Models -- Chapter 4. Dynamic Inventory Control Models -- Chapter 5. Lot-sizing Heuristics -- Chapter 6. Stochastic Inventory Models -- Part - III: Multi-item Inventory Models -- Chapter 7. Multi-item Inventory Models Subject to Constraints -- Chapter 8. Selective Inventory Control Models -- Part - IV: Advanced Inventory Models -- Chapter 9. Inventory Models for Perishable Items and Style Goods -- Chapter 10- Inventory Models for Maintenance and Repairable Items -- Chapter 11. Multiechelon Inventory Models.

This book presents a compilation of over 200 numerical problems and solutions that students can use to learn, practice and master the Inventory Control and Management concepts. Intended as a companion to any of the standard textbooks in Inventory Control and Management and written in simple language, it illustrates very clearly the steps students need to follow in order to solve a given problem. It also explains which solution methodologies can be used under which circumstances. Offering an ideal one-stop resource for mid-level engineering and business students who have taken Inventory Management or a related subject as an elective, this book is the only one students will ever need to prepare and gain confidence for their examinations in this subject.

Description based on publisher-supplied MARC data.

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