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Mathematics Colloquium: Computational complexity of stochastic programs

Speaker: Alexander Shapiro, Georgia Institute of Technology

Title: Computational complexity of stochastic programs

Abstract: The traditional approach to solving stochastic programming problems involves discretization of the underlying probability distributions. However, the number of required discretization points (called scenarios) grows exponentially both with increase of the number of random parameters and number of stages. In order to deal with this exponential explosion, randomization approaches based on Monte Carlo sampling techniques were developed. In this talk we discuss computational complexity of some of such methods from theoretical and practical points of view.

Time: Thursday, April 4, 2019, 10:50-11:50 a.m.

Place: Johnson Center, Room 334 (Meeting Room E) and Room 336 (Meeting Room F)

Coffee will be served at 10:20 a.m.