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|a Soft computing in inventory management /
|c Nita H. Shah, Mandeep Mittal, editors.
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| 264 |
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|a Singapore :
|b Springer,
|c [2021]
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| 264 |
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|c ©2021
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| 300 |
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|a 1 online resource :
|b illustrations (some color)
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1 |
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|a Inventory optimization,
|x 2730-9355
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| 520 |
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|a This book presents a collection of mathematical models that deals with the real scenario in the industries. The primary objective of this book is to explore various effective methods for inventory control and management using soft computing techniques. Inventory control and management is a very tedious task faced by all the organizations in any sector of the economy. It makes decisions for policies, activities, and procedures in order to make sure that the right amount of each item is held in stock at any time. Many industries suffer from indiscipline while ordering and production mismatch. It is essential to provide best ordering policy to control such kind of mismatch in the industries. All the mathematical model solutions are provided with the help of various soft computing optimization techniques to determine optimal ordering policy. This book is beneficial for practitioners, educators, and researchers. It is also helpful for retailers/managers for improving business functions and making more accurate and realistic decisions.
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|a Chapter 1. Retailer's Optimal Ordering Policy under Supplier Credits when Demand is Fuzzy and Cloud Fuzzy -- Chapter 2. An Application of PSO to Study joint policies of an Inventory Model with Demand Sensitive to Trade credit and Selling price while Deterioration of item being controlled using Preventive Technique -- Chapter 3. Optimization of the Berth allocation problem to the vessels using priority queuing systems -- Chapter 4. Fuzzy Inventory Model for Deteriorating Items in a Supply Chain System with Time Dependent Demand Rate -- Chapter 5. Credit financing in a two-warehouse inventory model with fuzzy deterioration and weibull demand -- Chapter 6. Two-Warehouse Inventory of Sugar industry Model for Deteriorating Items with Inflation using Differential Evolution -- Chapter 7. A Stackelberg Game Approach: In Supply Chain for Imperfect Quality Items with Learning Effect in Fuzzy Environment -- Chapter 8. An analytic and Genetic Algorithm Approach to optimize Integrated Production-Inventory Model under time-varying Demand -- Chapter 9. Sustainable Inventory Model with Carbon Emission Dependent Demand under Different Carbon Emission Policies -- Chapter 10. Impact of two different trade credits options on a supply chain with joint and independent decision under trapezoidal demand -- Chapter 11. A Co-Ordinated Single-Vendor Single-Buyer Inventory System with Deterioration and Freight Discounts.
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|a Online resource; title from PDF title page (SpringerLink, viewed August 27, 2021).
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| 650 |
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|a Inventory control
|x Mathematical models.
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| 650 |
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|a Soft computing.
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| 650 |
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7 |
|a Inventory control
|x Mathematical models
|2 fast
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| 650 |
|
7 |
|a Soft computing
|2 fast
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| 700 |
1 |
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|a Shah, Nita H.,
|e editor.
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| 700 |
1 |
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|a Mittal, Mandeep,
|d 1978-
|e editor.
|1 https://id.oclc.org/worldcat/entity/E39PCjJ76GDj8xx4pmgv7rdxpd
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| 758 |
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|i has work:
|a Soft computing in inventory management (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFMK7hwMYykhD4QPgybw4q
|4 https://id.oclc.org/worldcat/ontology/hasWork
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| 776 |
0 |
8 |
|i Print version:
|t Soft computing in inventory management.
|d Singapore : Springer, [2021]
|z 9811621551
|z 9789811621550
|w (OCoLC)1243349957
|
| 830 |
|
0 |
|a Inventory optimization.
|x 2730-9355
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-981-16-2156-7
|y Click for online access
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| 903 |
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|a SPRING-BUS2021
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| 994 |
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|b HCD
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