Monte Carlo sampling methods

A Shapiro - Handbooks in operations research and management …, 2003 - Elsevier
In this chapter we discuss Monte Carlo sampling methods for solving large scale stochastic
programming problems. We concentrate on the “exterior” approach where a random sample …

Monte Carlo sampling-based methods for stochastic optimization

T Homem-de-Mello, G Bayraksan - Surveys in Operations Research and …, 2014 - Elsevier
This paper surveys the use of Monte Carlo sampling-based methods for stochastic
optimization problems. Such methods are required when—as it often happens in practice …

[LIVRE][B] The cross-entropy method: a unified approach to combinatorial optimization, Monte-Carlo simulation, and machine learning

RY Rubinstein, DP Kroese - 2004 - Springer
This book is a comprehensive and accessible introduction to the cross-entropy (CE) method.
The CE method started life around 1997 when the first author proposed an adaptive …

[LIVRE][B] Theory of random sets

I Molchanov, IS Molchanov - 2005 - Springer
Stochastic geometry is a relatively new branch of mathematics. Although its predecessors
such as geometric probability date back to the 18th century, the formal concept of a random …

International Series in Operations Research & Management Science

FS Hillier, CC Price - 2005 - Springer
The beginning of stochastic programming, and in particular stochastic linear programming
(SLP), dates back to the 50's and early 60's of the last century. Pioneers who—at that time …

On the rate of convergence of optimal solutions of Monte Carlo approximations of stochastic programs

A Shapiro, T Homem-de-Mello - SIAM journal on optimization, 2000 - SIAM
In this paper we discuss Monte Carlo simulation based approximations of astochastic
programming problem. We show that if the corresponding random functions are convex …

Stochastic improvement of cyclic railway timetables

L Kroon, G Maróti, MR Helmrich, M Vromans… - … Research Part B …, 2008 - Elsevier
Real-time railway operations are subject to stochastic disturbances. Thus a timetable should
be designed in such a way that it can cope with these disturbances as well as possible. For …

Stability of stochastic programming problems

W Römisch - Handbooks in operations research and management …, 2003 - Elsevier
The behaviour of stochastic programming problems is studied in case of the underlying
probability distribution being perturbed and approximated, respectively. Most of the …

A stochastic model for the integrated optimization on metro timetable and speed profile with uncertain train mass

X Yang, A Chen, B Ning, T Tang - Transportation Research Part B …, 2016 - Elsevier
The integrated timetable and speed profile optimization model has recently attracted more
attention because of its good achievements on energy conservation in metro systems …

Quantitative stability in stochastic programming: The method of probability metrics

ST Rachev, W Römisch - Mathematics of Operations …, 2002 - pubsonline.informs.org
Quantitative stability of optimal values and solution sets to stochastic programming problems
is studied when the underlying probability distribution varies in some metric space of …