Advanced Linear Programming
Advanced Linear Programming covers polynomial time methods, quadratic programs, linear complementarity problems, solution set continuity, error bounds, and parallel algorithms.
Summary
Recent recorded grades — Fall 2014: 2.69 GPA, 75.0% A/AB (n=8 letter grades); Spring 2020: 3.75 GPA, 100.0% A/AB (n=6 letter grades).
What you’ll be able to do
Use the theory of linear programming to prove general duality results
Apply the concept of complementarity
Analyze and develop algorithms for solving optimization and equilibrium problems
Apply decomposition methods and other advanced algorithms for the solution of optimization and equilibrium problems
Understand economic concepts and how they relate to optimization and equilibria
Extend theory of linear programming into the framework of conic programming
Source: UW Guide 1· UW Guide 2
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapSTAT/COMP SCI/I SY E/MATH 525 and (COMP SCI 200, 220, 300, 301, 310, or placement into COMP SCI 300) or graduate/professional standing
- COMPSCI/ISYE/MATH/STAT 525
- COMPSCI 200
- COMPSCI 220
- COMPSCI 300
- 301
- COMPSCI 310
- placement into COMP SCI 300
- graduate/professional standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- All of
- COMPSCI/ISYE/MATH/STAT 525
- Any of
- COMPSCI 200
- COMPSCI 220
- COMPSCI 300
- 301
- COMPSCI 310
- placement into COMP SCI 300
- graduate/professional standing
- All of
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
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Student experience
the class
Recent recorded grades — Fall 2014: 2.69 GPA, 75.0% A/AB (n=8 letter grades); Spring 2020: 3.75 GPA, 100.0% A/AB (n=6 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Polynomial time methods for linear programming
- Quadratic programs and linear complementarity problems
- Solution sets and their continuity properties
- Error bounds for linear inequalities and programs
- Parallel algorithms for linear and quadratic programs
- Conic programming
Skills
- Prove general duality results using linear programming theory
- Apply the concept of complementarity
- Analyze and develop algorithms for solving optimization and equilibrium problems
- Apply decomposition methods and other advanced algorithms for optimization and equilibrium problems
- Understand economic concepts related to optimization and equilibria
- Extend linear programming theory into the framework of conic programming
Grades
Latest available · Spring 2020— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Spring 2020
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
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Raw records
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Student reviews
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Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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"observed_at": "2026-10-14 17:50:09.728220+00:00"
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