An integrated data-driven method using deep learning for a newsvendor problem with unobservable features
Year of publication: |
2022
|
---|---|
Authors: | Pirayesh Neghab, Davood ; Khayyati, Siamak ; Karaesmen, Fikri |
Published in: |
European journal of operational research : EJOR. - Amsterdam : Elsevier, ISSN 0377-2217, ZDB-ID 243003-4. - Vol. 302.2022, 2 (16.10.), p. 482-496
|
Subject: | Inventory | Hidden Markov model | Deep neural network | Partially observed data | Integrated estimation and optimization | Theorie | Theory | Lagerhaltungsmodell | Inventory model | Neuronale Netze | Neural networks | Markov-Kette | Markov chain | Stochastischer Prozess | Stochastic process |
-
A multi-item approach to repairable stocking and expediting in a fluctuating demand environment
Arts, Joachim, (2017)
-
A stochastic inventory system with two modes of service and retrail of customers
Rejitha, K. R., (2018)
-
A coordinated manufacturer-retailer model under stochastic demand and production rate
Sajadieh, Mohsen Sheikh, (2015)
- More ...
-
Data-driven control of a production system by using marking-dependent threshold policy
Khayyati, Siamak, (2020)
-
Production and energy mode control of a production-inventory system
Tan, Barış, (2023)
-
A machine learning approach for implementing data-driven production control policies
Khayyati, Siamak, (2022)
- More ...