An empirical analysis of scenario generation methods for stochastic optimization
From MaRDI portal
Publication:323497
DOI10.1016/j.ejor.2016.05.021zbMath1346.90643OpenAlexW2401215742MaRDI QIDQ323497
Publication date: 7 October 2016
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: http://epub.wu.ac.at/5594/1/Loehndorf_2016_Scenario_generation.pdf
stochastic optimizationMonte Carlo methodsprobability metricssample average approximationscenario generation
Related Items (15)
Non-convex multiobjective optimization under uncertainty: a descent algorithm. Application to sandwich plate design and reliability ⋮ A stochastic multiple gradient descent algorithm ⋮ Decision-based scenario clustering for decision-making under uncertainty ⋮ A diversity-based genetic algorithm for scenario generation ⋮ Importance sampling in stochastic optimization: an application to intertemporal portfolio choice ⋮ Uncertainty in maritime ship routing and scheduling: a literature review ⋮ Unnamed Item ⋮ A unified framework for stochastic optimization ⋮ A co-evolutionary matheuristic for the car rental capacity-pricing stochastic problem ⋮ Optimal operation of a CHP plant participating in the German electricity balancing and day-ahead spot market ⋮ Fostering long-term care planning in practice: extending objectives and advancing stochastic treatment within location-allocation modelling ⋮ Multiscale stochastic optimization: modeling aspects and scenario generation ⋮ Scenario generation by selection from historical data ⋮ A parallelized variable fixing process for solving multistage stochastic programs with progressive hedging ⋮ Scenario reduction revisited: fundamental limits and guarantees
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A method for simulating non-normal distributions
- The impact of sampling methods on bias and variance in stochastic linear programs
- Newsvendor solutions via conditional value-at-risk minimization
- A space quantization method for numerical integration
- A quantization algorithm for solving multidimensional discrete-time optimal stopping problems
- Epi-convergent discretizations of stochastic programs via integration quadratures
- A heuristic for moment-matching scenario generation
- Scenario reduction algorithms in stochastic programming
- Foundations of quantization for probability distributions
- A note on scenario reduction for two-stage stochastic programs
- Financial scenario generation for stochastic multi-stage decision processes as facility location problems
- Variance reduction in sample approximations of stochastic programs
- The empirical behavior of sampling methods for stochastic programming
- Generating Moment Matching Scenarios Using Optimization Techniques
- Optimal scenario tree reduction for stochastic streamflows in power generation planning problems
- Optimal Quantization for Finance: From Random Vectors to Stochastic Processes
- Introduction to Stochastic Programming
- Variance Reduction and Objective Function Evaluation in Stochastic Linear Programs
- Optimal quadratic quantization for numerics: the Gaussian case
- Comparison of Sampling Methods for Dynamic Stochastic Programming
- Algorithm 823
- L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
- Scenario tree generation for multiperiod financial optimization of optimal discretization
This page was built for publication: An empirical analysis of scenario generation methods for stochastic optimization