MATH 335
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Optimization
Department(s)
Course Description
This course is about how to find the best - or at least good - solutions to large problems frequently arising in business, industrial, or scientific settings. Students learn how to model these problems mathematically, algorithms for finding solutions to them, and the theory behind why the algorithms work. Topics include the simplex method, duality theory, sensitivity analysis, and network models. The focus is on linear models and models with combinatorial structure, but some nonlinear models are considered as well. Optimization software is used frequently.
Course Typically Offered
Offered every other year.
Career
Undergraduate
Prerequsites
000136
Catalog Course Attributes
CO24 - SCIMATH (Nat Sci and Math)
Min Units
1
Max Units
1
Name
Lecture
Optional Component
No
Final Exam Type
Yes