Spring 2027

Operations Research-deterministic Modeling

Operations Research-Deterministic Modeling covers basic techniques for modeling and optimizing deterministic systems with emphasis on linear programming, including computer solutions and applications to production, logistics, and service.

offering recorded3 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Jeff Linderoth

Students reported that homework took a long time and exams included difficult true and false questions. Success required understanding how to solve homework problems independently and attending lectures.

What you’ll be able to do

  • Write an algebraic formulation of an optimization model that captures the main decision elements of practical problems

  • Use an algebraic modeling language to solve an optimization model

  • Model logical constraints using binary decision variables

  • Understand the basic ideas behind algorithms for solving linear programming and discrete optimization problems

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

MATH 222 and (MATH 340, 341, 345 or 375), or member of Engineering Guest Students

ISYE 323 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

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

AMANDA SMITH is recorded teaching in Spring 2022, Spring 2023, Spring 2024, Spring 2025. Recorded history may be incomplete and does not establish a future schedule.

JEFFREY LINDEROTH is recorded teaching in Fall 2007, Fall 2008, Fall 2009, Fall 2010, Spring 2011, Spring 2012, Spring 2013, Fall 2013, Fall 2015, Spring 2016, Fall 2016, Fall 2017, Fall 2018, Fall 2019, 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 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 500
DIS 303Classroom Instruction0 / 250
DIS 301Classroom Instruction0 / 250

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

Past student reviews · Amanda Smith

Amanda Smith focused on underlying concepts rather than mastery, making a historically difficult class manageable. Students found her instruction engaging and effective at breaking down complicated subjects.

Recent recorded grades — Spring 2025: 3.16 GPA, 52.8% A/AB (n=53 letter grades); Fall 2025: 3.12 GPA, 32.7% A/AB (n=52 letter grades); Spring 2026: 3.18 GPA, 48.8% A/AB (n=41 letter grades).

difficulty & workload

Past student reviews · Jeff Linderoth

Students reported that homework took a long time and exams included difficult true and false questions. Success required understanding how to solve homework problems independently and attending lectures.

Past student reviews · Jeff Linderoth

Jeff Linderoth's assignments were sometimes confusing, but he was helpful during office hours. While attendance was not mandatory, one student felt they could not do well without attending lecture.

Topics

  • Linear programming
  • Computer solution of optimization problems
  • Applications to production, logistics, and service systems
  • Algorithms for linear programming and discrete optimization

Skills

  • Formulating optimization models for practical problems
  • Solving optimization models using algebraic modeling languages
  • Modeling logical constraints with binary decision variables
  • Applying linear programming to production, logistics, and service systems

Grades

Historical instructor

Spring 2027 · 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.

7 earlier forecasts · 0.10 GPA average error.

Grades over time

Through Spring 2027

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

1280 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
ISYE 323 · Spring 2027

Operations Research-Deterministic Modeling

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:490:010235",
    "course_id": "ISYE 323",
    "course_uid": "course_2f334f3968bc9545732db707",
    "term_id": "1274",
    "source_course_id": "010235",
    "source_subject_id": "490",
    "title": "Operations Research-Deterministic Modeling",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Fall, Spring"
  }
]
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 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1Download part 2Download part 3Download part 4
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "e24f6fadff685fb927262a54daa0bf33246988592d9b851d7a539ad117123bf4",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}