Updated-Absolute Expected Value Solution Approach for multistage stochastic programming�problems

Gespeichert in:
Bibliographische Detailangaben
Titel: Updated-Absolute Expected Value Solution Approach for multistage stochastic programming�problems
Autoren: Yasuhiro Shoji, Selen Cremaschi
Quelle: Systems and Control Transactions. 4:1275-1280
Verlagsinformationen: PSE Press, 2025.
Publikationsjahr: 2025
Beschreibung: This paper introduces the Updated Absolute Expected Value Solution, U-AEEV, a heuristic for solving multi-stage stochastic programming (MSSP) problems with type 2 endogenous uncertainty. U-AEEV is an evolution of the Absolute Expected Value Solution, AEEV [1]. This paper aims to show how U-AEEV overcomes the drawbacks of AEEV and performs better than AEEV. To demonstrate the performance of U-AEEV, we solve 6 MSSP problems with type 2 endogenous uncertainty and compare the solutions and computational resource requirements.
Publikationsart: Article
ISSN: 2818-4734
DOI: 10.69997/sct.188893
Dokumentencode: edsair.doi...........762f37a5fd80c97a36fe7fd5ff1e4e31
Datenbank: OpenAIRE