On minimax solutions of stochastic linear programming problems
Multistage stochastic programs: The state-of-the-art and selected bibliography
On maximizing a concave function subject to linear constraints by Newton's method
On non-normal asymptotic behavior of optimal solutions for stochastic programming problems and on related problems of mathematical statistics
Risk objectives in two-stage stochastic programming models
In applications of stochastic programming, optimization of the expected outcome need not be an acceptable goal. This has been the reason for recent proposals aiming at construction and optimization of more complicated nonlinear risk objectives. We will survey various approaches to risk quantification and optimization mainly in the framework of static and two-stage stochastic programs and comment on their properties. It turns out that polyhedral risk functionals introduced in Eichorn and Römisch...
Stochastic geometric programming with an application
In applications of geometric programming, some coefficients and/or exponents may not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which stochastic programming approaches and which structural and distributional assumptions do not destroy the favorable structure of geometric programs. The already recognized possibilities are extended for a tracking model and stochastic sensitivity analysis is presented in the context...
Stability in stochastic programming with recourse
Special issue: Stochastic Programming in EURO XXII in Prague
Současná ekonometrie jako součást matematiky
On estimating the yield and volatility curves
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