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The elements of joint learning and o...
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Chen, Xi.
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The elements of joint learning and optimization in operations management
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The elements of joint learning and optimization in operations management/ edited by Xi Chen, Stefanus Jasin, Cong Shi.
其他作者:
Chen, Xi.
出版者:
Cham :Springer International Publishing : : 2022.,
面頁冊數:
xiii, 444 p. :ill. (some col.), digital ;24 cm.
內容註:
Part 1: Generic Tools -- Chapter 1: The Stochastic Multi-armed Bandit Problem -- Chapter 2: Reinforcement Learning -- Chapter 3: Optimal Learning and Optimal Design -- Part 2: Price Optimization -- Chapter 4: Dynamic Pricing with Demand Learning: Emerging Topics and State of the Art -- Chapter 5: Learning and Pricing with Inventory Constraints -- Chapter 6: Dynamic Pricing and Demand Learning in Nonstationary Environments -- Chapter 7: Pricing with High-Dimensional Data -- Part 3: Assortment Optimization -- Chapter 8: Nonparametric Estimation of Choice Models -- Chapter 9: The MNL-Bandit Problem -- Chapter 10: Dynamic Assortment Optimization: Beyond MNL Model -- Part 4: Inventory Optimization -- Chapter 11: Inventory Control with Censored Demand -- Chapter 12: Joint Pricing and Inventory Control with Demand Learning -- Chapter 13: Optimization in the Small-Data, Large-Scale Regime -- Part 5: Healthcare Operations -- Chapter 14: Bandit Procedures for Designing Patient-Centric Clinical Trials -- Chapter 15: Dynamic Treatment Regimes.
Contained By:
Springer Nature eBook
標題:
Production management. -
電子資源:
https://doi.org/10.1007/978-3-031-01926-5
ISBN:
9783031019265
The elements of joint learning and optimization in operations management
The elements of joint learning and optimization in operations management
[electronic resource] /edited by Xi Chen, Stefanus Jasin, Cong Shi. - Cham :Springer International Publishing :2022. - xiii, 444 p. :ill. (some col.), digital ;24 cm. - Springer series in supply chain management,v. 182365-6409 ;. - Springer series in supply chain management ;v. 18..
Part 1: Generic Tools -- Chapter 1: The Stochastic Multi-armed Bandit Problem -- Chapter 2: Reinforcement Learning -- Chapter 3: Optimal Learning and Optimal Design -- Part 2: Price Optimization -- Chapter 4: Dynamic Pricing with Demand Learning: Emerging Topics and State of the Art -- Chapter 5: Learning and Pricing with Inventory Constraints -- Chapter 6: Dynamic Pricing and Demand Learning in Nonstationary Environments -- Chapter 7: Pricing with High-Dimensional Data -- Part 3: Assortment Optimization -- Chapter 8: Nonparametric Estimation of Choice Models -- Chapter 9: The MNL-Bandit Problem -- Chapter 10: Dynamic Assortment Optimization: Beyond MNL Model -- Part 4: Inventory Optimization -- Chapter 11: Inventory Control with Censored Demand -- Chapter 12: Joint Pricing and Inventory Control with Demand Learning -- Chapter 13: Optimization in the Small-Data, Large-Scale Regime -- Part 5: Healthcare Operations -- Chapter 14: Bandit Procedures for Designing Patient-Centric Clinical Trials -- Chapter 15: Dynamic Treatment Regimes.
This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.
ISBN: 9783031019265
Standard No.: 10.1007/978-3-031-01926-5doiSubjects--Topical Terms:
518951
Production management.
LC Class. No.: TS155 / .E54 2022
Dewey Class. No.: 658.5
The elements of joint learning and optimization in operations management
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