Tuesday, May 11

Probabilistic Constrained Optimization - Part I of II

10:45 AM-12:45 PM
Room: Atlanta 5

For Part II, see MS31.

Optimization problems with probabilistic performance functions and constraints play an important role in several applications, such as, nuclear safety (core melt probability), ecology (extinction probability), environment (95% estimates of allowed doze), and finance (value-at-risk). Although these problems are very important, they attract relatively little interest from the optimization community because of their complexity. Recently, significant advances have been made in optimization and sensitivity analysis of the probabilistic functions, which is the basis for construction of new efficient optimization approaches. For instance, analytical formulas for the derivatives of probability functions have been developed and applied in Probabilistic Risk Analysis. The speakers in this minisymposium will present the state-of-the-art in probabilistic constrained optimization.

Organizer: Stanislav Uryasev
University of Florida

10:45-11:10 UpdatedSimulataneous Calculation of Sensitivities of Value-at-Risk Using Monte-Carlo and Numerical
MethodsStanislav Uryasev, Organizer
11:15-11:40 The Use of Discrete Moment Bounds in Probabilistic Constrained Stochastic Programming Models
András Prékopa, Rutgers University
11:45-12:10 On Stochastic Integer Programming Problems Under Probabilistic Constraints
Darinka Dentcheva, András Prékopa, and A. Ruszczynski, Rutgers University
CANCELLED 12:15-12:40 Discrete Approximation of a Linear Two-stage Problem with Quantile Function
Andrei Kibzun, Moscow State Aviation Institute, Russia

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MMD, 3/15/99