Fall 2026

Operations Research-deterministic Modeling

ISYE 323 teaches basic techniques for modeling and optimizing deterministic systems, emphasizing linear programming and its applications.

offering recorded3 credits
Recorded instructors · Fall 2026 Jim Luedtke3.9/5

Summary

1 / 7

The course is challenging, with very time-consuming case studies and hard material. Students report that the homework is relevant but requires significant effort to master the content.

Grade history

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average GPA
letter grades
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AB
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All recorded terms · compare terms & instructors

Prerequisites

Course map

MATH 222 and (MATH 340, 341 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

Fall 2026
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.57/5 from 7 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: 4.5/5 raw quality · 3.0/5 difficulty · 6 reviews

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

Jim Luedtke is praised for detailed explanations, clear examples, and engaging lectures. Reviewers note his helpfulness in office hours and willingness to accommodate schedules. However, the material is challenging, and one reviewer reports he can be condescending to non-experts.

Historical instructors & teaching patterns

Amanda Smith is described as engaging and excellent at breaking down complicated subjects, making the historically difficult course manageable. Reviewers highlight her fairness, helpfulness during office hours, and focus on underlying concepts rather than excessive difficulty.

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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction66 / 563
DIS 301Classroom Instruction34 / 282

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

Jim Luedtke provides clear lectures and detailed examples that make the material understandable. One reviewer found him rude and condescending to those lacking optimization expertise.

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

The course is challenging, with very time-consuming case studies and hard material. Students report that the homework is relevant but requires significant effort to master the content.

Some students appreciate that Luedtke corrects mistakes in notes and exams when asked, while others report being ridiculed for asking questions.

Topics

  • Linear programming
  • Production, logistics, and service systems

Skills

  • Modeling and optimizing deterministic systems.
  • Computer solution of optimization problems.
  • Applying optimization to production, logistics, and service systems.

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 · 0.11 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
ISYE 323 · Fall 2026

Operations Research-Deterministic Modeling

Recorded 2026-09-07
Raw records 
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:490:010235",
    "course_id": "ISYE 323",
    "course_uid": "course_2f334f3968bc9545732db707",
    "term_id": "1272",
    "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 2026-09-07

View the dataset on Hugging Face
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.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "e2157be5212d7066d09cc1736562a2c4268a48161355c49af58a55af059a8871",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}