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STOCHASTIC PROGRAMMING

COMPSCI/ISYE 719
Course Description

Stochastic programming is concerned with decision making in the presence of uncertainty, where the eventual outcome depends on a future random event. Topics include modeling uncertainty in optimization problems, risk measures, stochastic programming algorithms, approximation and sampling methods, and applications. Students are strongly encouraged to have knowledge of linear programming (e.g.,MATH/​COMP SCI/​I SY E/​STAT  525) and probability and statistics (e.g.,MATH/​STAT  431). Knowledge of integer optimization (MATH/​COMP SCI/​I SY E  728) is helpful, but not required.

Prerequisties

Graduate/professional standing

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average
3.35

-3.31% from Historical

Completion Rate
100%

No change from Historical

A Rate
73.08%

5.99% from Historical

Class Size
26

23.16% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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