Integer Optimization
Recorded 2026-10-14Integer Optimization
Integer Optimization introduces integer optimization problems and surveys algorithm theory, focusing on polyhedral formulations, algebraic/geometric properties, and combinatorial optimization applications.
Summary
Past student reviews · Alberto Del Pia
Homeworks were described as very manageable and instructive, while exams were noted as the challenging aspect of the course.
What you’ll be able to do
Describe and explain the basics of polyhedral theory, which consists in the study of systems of linear inequalities both from an algebraic and a geometric point of view
Define perfect formulations and identify what properties are desirable in an integer programming formulation of a problem
Explain how valid inequalities can be used as cutting planes to strengthen integer programming formulations
Source: UW Guide 1· UW Guide 2· UW Guide 3
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing
- Graduate/professional standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Graduate/professional standing
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
ALBERTO DEL PIA is recorded teaching in Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.
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 |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 0 / 25 | 0 |
| LEC 001 | Classroom Instruction | 0 / 25 | 0 |
| LEC 001 | Classroom Instruction | 0 / 25 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Meeting source records
Student experience
the class
Past student reviews · Alberto Del Pia
Alberto Del Pia taught this course as an encouraging professor who cared deeply about the subject matter. He was known for providing great intuition for deep proofs and responding to student questions in detail.
Recent recorded grades — Spring 2024: 3.54 GPA, 69.6% A/AB (n=23 letter grades); Spring 2025: 3.50 GPA, 68.4% A/AB (n=19 letter grades); Spring 2026: 3.57 GPA, 80.0% A/AB (n=15 letter grades).
difficulty & workload
Past student reviews · Alberto Del Pia
Homeworks were described as very manageable and instructive, while exams were noted as the challenging aspect of the course.
Past student reviews · Alberto Del Pia
Students appreciated the professor's encouraging atmosphere for asking questions, though one noted the inconvenience of the class moving online during the pandemic.
Topics
- Formulations, relaxations, polyhedral theory, cutting planes, decomposition, enumeration
- Applications in combinatorial optimization
Skills
- Explain the basics of polyhedral theory for systems of linear inequalities
- Define perfect formulations and identify desirable properties in integer programming formulations
- Explain how valid inequalities function as cutting planes to strengthen integer programming formulations
Grades
Latest available · Spring 2026— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Spring 2026
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
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
Integer Optimization
Recorded 2026-10-14Integer Optimization
Recorded 2026-10-14Raw records
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]Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
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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