Parallel Nonstationary Direct Policy Search for Risk-Averse Stochastic Optimization
| Autor: | Boris Defourny, Warren B. Powell, Belgacem Bouzaiene-Ayari, Somayeh Moazeni |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
021103 operations research Optimization problem Optimality criterion 020209 energy 0211 other engineering and technologies General Engineering 02 engineering and technology Multi-objective optimization Stochastic programming Dynamic programming Derivative-free optimization 0202 electrical engineering electronic engineering information engineering Stochastic optimization Metaheuristic Mathematics |
| Zdroj: | INFORMS Journal on Computing. 29:332-349 |
| ISSN: | 1526-5528 1091-9856 |
| DOI: | 10.1287/ijoc.2016.0733 |
| Popis: | This paper presents an algorithmic strategy to nonstationary policy search for finite-horizon, discrete-time Markovian decision problems with large state spaces, constrained action sets, and a risk-sensitive optimality criterion. The methodology relies on modeling time-variant policy parameters by a nonparametric response surface model for an indirect parametrized policy motivated by Bellman’s equation. The policy structure is heuristic when the optimization of the risk-sensitive criterion does not admit a dynamic programming reformulation. Through the interpolating approximation, the level of nonstationarity of the policy, and consequently, the size of the resulting search problem can be adjusted. The computational tractability and the generality of the approach follow from a nested parallel implementation of derivative-free optimization in conjunction with Monte Carlo simulation. We demonstrate the efficiency of the approach on an optimal energy storage charging problem, and illustrate the effect of the risk functional on the improvement achieved by allowing a higher complexity in time variation for the policy. The online supplement is available at https://doi.org/10.1287/ijoc.2016.0733 . |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|