Performance comparison of approximate dynamic programming techniques for dynamic stochastic scheduling
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Dosyalar
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Balikesir University
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper focuses on the performance comparison of several approximate dynamic programming (ADP) techniques. In particular, we evaluate three ADP techniques through a class of dynamic stochastic scheduling problems: Lagrangian-based ADP, linear programming-based ADP, and direct search-based ADP. We uniquely implement the direct search-based ADP through basis functions that differ from those used in the relevant literature. The class of scheduling problems has the property that jobs arriving dynamically and stochastically must be scheduled to days in advance. Numerical results reveal that the direct search-based ADP outperforms others in the majority of problem sets generated.
Açıklama
Anahtar Kelimeler
Approximate Dynamic Programming, Dynamic Stochastic Scheduling, Markov Decision Processes
Kaynak
International Journal of Optimization and Control: Theories and Applications
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
11
Sayı
2
Künye
Göçgün, Y. (2021). Performance comparison of approximate dynamic programming techniques for dynamic stochastic scheduling. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 11(2), 178-185.
