Stratified filtered sampling in stochastic optimization

13 years 4 months ago

Download www.rpi.edu

We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distribution of performance associated with the strategy, and define an appropriate stratified sampling plan. An algorithm we call filtered search allows us to implement this plan efficiently. We demonstrate the approach's advantages with a problem in asset / liability management for an insurance company.

Robert Rush, John M. Mulvey, John E. Mitchell, Tho

Real-time Traffic

Decision Strategy | JAMDS 2000 | Methodology | Stochastic Optimization Model |

claim paper

» Joint Tracking of Pose Expression and Texture using Conditionally Gaussian Filters

» Smart Particle Filtering for 3D Hand Tracking

» Image Segmentation by Shape Particle Filtering

» Smart particle filtering for highdimensional tracking

» Particle methods for Bayesian modeling and enhancement of speech signals

» Shape Particle Filtering for Image Segmentation

» Estimation from lossy sensor data jump linear modeling and Kalman filtering

» Object tracking and detection after occlusion via numerical hybrid local and global modese...

Post Info
More Details (n/a)

Added	18 Dec 2010
Updated	18 Dec 2010
Type	Journal
Year	2000
Where	JAMDS
Authors	Robert Rush, John M. Mulvey, John E. Mitchell, Thomas R. Willemain

Comments (0)

Sciweavers

Stratified filtered sampling in stochastic optimization

Decision Strategy | JAMDS 2000 | Methodology | Stochastic Optimization Model |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers