Fall 2026

Linear Optimization

Introduces linear optimization problems, emphasizing formal proofs, the simplex method, duality theory, and theorems of the alternatives.

offering recorded3 credits
Recorded instructors · Fall 2026 Alberto Del Pia3.8/5

Summary

1 / 6

The course is considered very difficult, with hard assignments that require significant study time, though group work is permitted. Exams are reported as easier than homework, although one student found the final exam unexpectedly difficult despite its stated format.

Grade history

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average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

MATH 320, 340, 341, 375, or443 or graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program

COMPSCI/ISYE/MATH/STAT 525 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 4.00/5 from 8 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 3.7/5 raw quality · 3.7/5 difficulty · 6 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Alberto Del Pia is described as a nice, caring, and amazing instructor who is passionate about the topics and teaches an organized course. Reviewers highlight his positive attitude and clear structure.

Some students find the course difficult due to heavy mathematical proofs and confusing lectures that are harder to follow than the textbook. One reviewer noted the final exam format was misleading compared to midterms.

Recent recorded grades — Fall 2023: 2.80 GPA, 47.0% A/AB (n=66 letter grades); Fall 2024: 2.97 GPA, 41.3% A/AB (n=63 letter grades); Fall 2025: 2.90 GPA, 39.1% A/AB (n=64 letter grades).

Historical instructors & teaching patterns

Alberto Del Pia has no reviews in the provided data. Historical reviews for Jesse Holzer, Shi Jin, and Michael Ferris describe confusing lectures, poor grading, and mistakes. Stephen Wright and Carla Michini received positive feedback for clarity and helpfulness, though Michini's homework was noted as difficult.

ALBERTO DEL PIA is recorded teaching in Fall 2017, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

CARLA MICHINI is recorded teaching in Spring 2018, Spring 2019, Spring 2020, Spring 2022, Fall 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

JESSE THOMAS HOLZER is recorded teaching in Fall 2013. Recorded history may be incomplete and does not establish a future schedule.

MICHAEL FERRIS is recorded teaching in Fall 2006, Fall 2007, Fall 2008, Spring 2010, Spring 2012, Spring 2013, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.

SHI JIN is recorded teaching in Spring 2015. Recorded history may be incomplete and does not establish a future schedule.

STEPHEN WRIGHT is recorded teaching in Spring 2008, Spring 2009, Fall 2009, Fall 2010, Fall 2012, Spring 2014, Fall 2014, Fall 2015, Spring 2017. 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction27 / 1100
LEC 001Classroom Instruction15 / 1101
LEC 001Classroom Instruction38 / 1100
LEC 001Classroom Instruction4 / 1100

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

Students describe Alberto Del Pia as a nice, caring, and amazing instructor who teaches an organized and well-structured course. They highly recommend the class for its supportive teaching style.

Recent recorded grades — Spring 2025: 3.02 GPA, 43.2% A/AB (n=74 letter grades); Fall 2025: 2.90 GPA, 39.1% A/AB (n=64 letter grades); Spring 2026: 3.12 GPA, 46.2% A/AB (n=52 letter grades).

difficulty & workload

The course is considered very difficult, with hard assignments that require significant study time, though group work is permitted. Exams are reported as easier than homework, although one student found the final exam unexpectedly difficult despite its stated format.

Lectures use slides that some find confusing compared to the textbook, with pacing varying between too fast and too slow. While the instructor is knowledgeable, students report that understanding the lectures can be harder than reading the assigned text.

Topics

  • Linear inequality constraints
  • Geometric and algebraic problem structure
  • Formal proofs
  • Simplex method theory
  • Duality theory and theorems of the alternatives

Skills

  • Developing geometric and algebraic insights into optimization problem structures.
  • Understanding the theory behind the simplex method.
  • Exploring duality theory and theorems of the alternatives.

Grades

Historical instructor

Fall 2026 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.10 GPA average error.

Grades over time

Through Fall 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1283 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

Sources & history

UW–Madison

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.

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Selected offering source records
COMPSCI/ISYE/MATH/STAT 525 · Fall 2026

Linear Optimization

Recorded 2026-09-07
COMPSCI/ISYE/MATH/STAT 525 · Fall 2026

Linear Optimization

Recorded 2026-09-07
COMPSCI/ISYE/MATH/STAT 525 · Fall 2026

Linear Optimization

Recorded 2026-09-07
COMPSCI/ISYE/MATH/STAT 525 · Fall 2026

Linear Optimization

Recorded 2026-09-07
Raw records
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    "term_id": "1272",
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    "source_subject_id": "266",
    "title": "Linear Optimization",
    "credits_min": 3,
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    "credits_min": 3,
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]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "363136421555bef5000e17618be7418a28f411ff5999b41f88c1bbf27807108e",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}