Sequential resource allocation for humanitarian operations using approximate dynamic programming
| Year of publication: |
2025
|
|---|---|
| Authors: | Fadaki, Masih ; Ansari, Sina ; Abareshi, Ahmad ; Lee, Paul T.-W. |
| Published in: |
Transportation research : an international journal. - Oxford : Pergamon, Elsevier Science, ISSN 1878-5794, ZDB-ID 2013782-5. - Vol. 201.2025, Art.-No. 104213, p. 1-27
|
| Subject: | Markov decision process | Equity | Reinforcement learning | Approximate dynamic programming | Humanitarian supply chain | Sequential resource allocation | Lieferkette | Supply chain | Humanitäre Hilfe | Humanitarian aid | Dynamische Optimierung | Dynamic programming | Allokation | Allocation | Markov-Kette | Markov chain | Mathematische Optimierung | Mathematical programming | Theorie | Theory | Entscheidung | Decision |
-
A review of approximate dynamic programming applications within military operations research
Rempel, M., (2021)
-
Optimising darts strategy using Markov decision processes and reinforcement learning
Baird, Graham, (2020)
-
Heatmap design for probabilistic driver repositioning in crowdsourced delivery
Alnaggar, Aliaa, (2025)
- More ...
-
Multi-period vaccine allocation model in a pandemic : a case study of COVID-19 in Australia
Fadaki, Masih, (2022)
-
World shipping and port development
Lee, Paul T.-W., (2005)
-
Shipping developments in Far East Asia : the Korean experience
Lee, Paul T.-W., (1996)
- More ...