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Optimization and Inventory Management

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Cover of 'Optimization and Inventory Management'

Table of Contents

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    Book Overview
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    Chapter 1 Economic Production Quantity (EPQ) Inventory Model for a Deteriorating Item with a Two-Level Trade Credit Policy and Allowable Shortages
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    Chapter 2 An Economic Order Quantity (EOQ) Inventory Model for a Deteriorating Item with Interval-Valued Inventory Costs, Price-Dependent Demand, Two-Level Credit Policy, and Shortages
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    Chapter 3 Inventory Control Policies for Time-Dependent Deteriorating Item with Variable Demand and Two-Level Order Linked Trade Credit
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    Chapter 4 Inventory Modelling of Deteriorating Item and Preservation Technology with Advance Payment Scheme Under Quadratic Demand
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    Chapter 5 Dynamic Pricing, Advertisement Investment and Replenishment Model for Deteriorating Items
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    Chapter 6 A Production Reliable Model for Imperfect Items with Random Machine Breakdown Under Learning and Forgetting
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    Chapter 7 Inventory Policies with Development Cost for Imperfect Production and Price-Stock Reliability-Dependent Demand
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    Chapter 8 Imperfect Quality Item Inventory Models Considering Carbon Emissions
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    Chapter 9 Non-instantaneous Deteriorating Model for Stock-Dependent Demand with Time-Varying Holding Cost and Random Decay Start Time
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    Chapter 10 Stock-Dependent Inventory Model for Imperfect Items Under Permissible Delay in Payments
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    Chapter 11 Joint Effects of Carbon Emission, Deterioration, and Multi-stage Inspection Policy in an Integrated Inventory Model
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    Chapter 12 A Note on “Inventory and Shelf-Space Optimization for Fresh Produce with Expiration Date Under Freshness-and-Stock-Dependent Demand Rate”
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    Chapter 13 EOQ Model Under Discounted Partial Advance—Partial Trade Credit Policy with Price-Dependent Demand
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    Chapter 14 Effects of Pre- and Post-Deterioration Price Discounts on Selling Price in Formulation of an Ordering Policy for an Inventory System: A Study
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    Chapter 15 Efficient Supplier Selection: A Way to Better Inventory Control
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    Chapter 16 Supply Chain Network Optimization Through Player Selection Using Multi-objective Genetic Algorithm
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    Chapter 17 Allocation of Order Amongst Available Suppliers Using Multi-objective Genetic Algorithm
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    Chapter 18 Some Studies on EPQ Model of Substitutable Products Under Imprecise Environment
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    Chapter 19 An Effective MILP Model for Food Grain Inventory Transportation in India—A Heuristic Approach
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    Chapter 20 Fuzzy Based Inventory Model with Credit Financing Under Learning Process
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    Chapter 21 A Fuzzy Two-Echelon Supply Chain Model for Deteriorating Items with Time Varying Holding Cost Involving Lead Time as a Decision Variable
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    Chapter 22 Transportation-Inventory Model for Electronic Markets Under Time Varying Demand, Retailer’s Incentives and Product Exchange Scheme
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    Chapter 23 Electronic Components’ Supply Chain Management of Electronic Industrial Development for Warehouse and Its Impact on the Environment Using Particle Swarm Optimization Algorithm
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    Chapter 24 Interpretive Structural Modeling to Understand Factors Influencing Buying Behavior of Air Freshener
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    Chapter 25 Decision-Making with Temporal Association Rule Mining and Clustering in Supply Chains
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Title
Optimization and Inventory Management
Published by
Springer Singapore, November 2019
DOI 10.1007/978-981-13-9698-4
ISBNs
978-9-81-139697-7, 978-9-81-139698-4
Editors

Shah, Nita H., Mittal, Mandeep

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 29%
Student > Bachelor 4 24%
Student > Ph. D. Student 2 12%
Researcher 1 6%
Professor > Associate Professor 1 6%
Other 1 6%
Unknown 3 18%
Readers by discipline Count As %
Engineering 6 35%
Business, Management and Accounting 4 24%
Arts and Humanities 1 6%
Chemistry 1 6%
Computer Science 1 6%
Other 0 0%
Unknown 4 24%