ORF 311 na, npdf
Optimization under Uncertainty
A survey of quantitative approaches for making optimal decisions under uncertainty, including decision trees, Monte Carlo simulation, and stochastic programs. Forecasting and planning systems are integrated with a focus on financial applications.
Sample reading list:
F. Hillier & G. Lieberman, Introduction to Operation Research 9th Ed.
Handouts:, Multi-objective optimization, optimization under uncertainty
Birge and Louveaux, Introduction to Stochastic Programming
Winston & Albright, Practical Management Science
Students will be required to design and build stochastic optimization models using Excel Add-ins and other software systems. A series of case studies will be discussed in precepts. Students are expected to read 25 pages per week.
Mid Term Exam - 25%
Final Exam - 40%
Programming Assignments - 10%
Problem set(s) - 25%
Open to Juniors and Seniors Only.
Prerequisites and Restrictions:
ORF 307 or MAT 305, and ORF 309.
|20380||L01||3:00 pm - 4:20 pm||T Th||Sherrerd Hall 101||Enrolled:36 Limit:40|
|P01||7:30 pm - 8:20 pm||M||Sherrerd Hall 001||Enrolled:0 Limit:20|
|P02||7:30 pm - 8:20 pm||W||Engineering Quad E-Wing E225||Enrolled:0 Limit:20|