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

TOINT, Philippe (PI)
BASTIN, Fabian (Researcher)

University of Namur

Project: Research

Project Details

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.

Status	Finished
Effective start/end date	29/03/02 → 31/12/07

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Keywords

Monte-Carlo
stochastic programming
trust-region
nonlinear programming

2 Article
1 Other report
1 Chapter

Estimating nonparametric random utility models with an application to the value of time in heterogeneous populations
Bastin, F., Cirillo, C. & Toint, P., 1 Nov 2010, In: Transportation Science. 44, 4, p. 537-549 13 p.
Research output: Contribution to journal › Article › peer-review

File
39 Downloads (Pure)
Application of an adaptive Monte Carlo algorithm to mixed logit estimation
Bastin, F., Cirillo, C. & Toint, P., 1 Aug 2006, In: Transportation Research Part B : Methodological. 40, 7, p. 577-593 17 p.
Research output: Contribution to journal › Article › peer-review

File
82 Downloads (Pure)
Estimating mixed logit with non-parametric random variables
Bastin, F., Cirillo, C. & Toint, P., 2006, Namur: FUNDP, Faculté des Sciences. Département de Mathématique. (Technical Report; vol. 06)
Research output: Book/Report/Journal › Other report

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

Description

Keywords

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

Application of an adaptive Monte Carlo algorithm to mixed logit estimation

Estimating mixed logit with non-parametric random variables