Name
Abstract | ||
|---|---|---|
In this paper, we consider expected value, variance and worst–case optimization of nonlinear models. We present algorithms for computing optimal expected value, and variance policies, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies based on expected value optimization and worst–case robustness. The latter is a minimax strategy and ensures optimal cover in view of the worst–case scenario(s) while the former is optimal expected performance in a stochastic setting.
Both approaches are used with a small macroeconomic model to illustrate relative performance, robustness and trade-offs between the alternative policies.
|
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10589-007-9136-7 | Computational Optimization and Applications |
Keywords | Field | DocType |
iterative taylor expansion,case robustness,relative performance,variance policy,relative merit,alternative policy,expected value optimization,case optimization,case analysis,expected value · worst-case analysis · policy design,variance optimization,linear system,case scenario,optimal expected value,expected value,taylor expansion | Convergence (routing),Mathematical optimization,Minimax,Macroeconomic model,Nonlinear system,Robustness (computer science),Expected value,Mathematics,Case analysis,Taylor series | Journal |
Volume | Issue | ISSN |
43 | 2 | 0926-6003 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Panos Parpas | 1 | 107 | 15.45 |
| B. Rustem | 2 | 27 | 5.64 |
| volker wieland | 3 | 0 | 0.34 |
| S. Žaković | 4 | 32 | 8.91 |