Use of Monte-Carlo sampling within trust-region methods, for the solving of nonlinear stochastic programming problems

Project: Research

Description

The goal of this project is to combine Monte-Carlo sampling techniques with trust-region methods in order to efficiently solve nonlinear stochastic programming problems.
StatusFinished
Effective start/end date29/03/02 → 31/12/07
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Keywords

  • Monte-Carlo
  • stochastic programming
  • trust-region
  • nonlinear programming

Related content

Research Output

Application of an adaptive Monte Carlo algorithm to mixed logit estimation

Research output: Contribution to journal › Article

Estimating nonparametric random utility models with an application to the value of time in heterogeneous populations

Research output: Contribution to journal › Article

An adaptive Monte-Carlo algorithm for computing mixed logit estimators

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Chapter

Estimating mixed logit with non-parametric random variables

Research output: Book/Report/Journal › Other report