An empirical analysis of scenario generation methods for stochastic optimization
Year of publication: |
16 November 2016
|
---|---|
Authors: | Löhndorf, Nils |
Published in: |
European journal of operational research : EJOR. - Amsterdam : Elsevier, ISSN 0377-2217, ZDB-ID 243003-4. - Vol. 255.2016, 1 (16.11.), p. 121-132
|
Subject: | Stochastic optimization | Sample average approximation | Scenario generation | Probability metrics | Monte Carlo methods | Stochastischer Prozess | Stochastic process | Theorie | Theory | Monte-Carlo-Simulation | Monte Carlo simulation | Mathematische Optimierung | Mathematical programming |
-
Importance sampling in stochastic optimization : an application to intertemporal portfolio choice
Ekblom, J., (2020)
-
Importance sampling in stochastic programming : a Markov chain Monte Carlo approach
Parpas, Panos, (2015)
-
Bayesian failure-rate modeling and preventive maintenance optimization
Belyi, Dmitriy, (2017)
- More ...
-
Machine and labor flexibility in manufacturing networks
Francas, David, (2011)
-
Löhndorf, Nils, (2014)
-
Modeling time-dependent randomness in stochastic dual dynamic programming
Löhndorf, Nils, (2019)
- More ...