Course content

• Syllabus [PDF]
• Lecture notes and materials
• Homework assignments
• Projects
• Exam topics

Course information

• Course name: CSCI 35500: Intro to Linear Programming
• Course mode of instruction: In person
• Class days and times: Mon/Wed 7:00-8:15 PM
• Class location: North 1001F
• Prerequisites:
  • CSCI 127 - Introduction to computer science (Python)
  • CSCI 150 - Discrete structures
  • MATH 160 - Matrix algebra

Instructor contact information

• Instructor name: Ben Rosenberg
• Instructor email address: benjamin.rosenberg24@myhunter.cuny.edu
• Office hours: Saturday, 4PM - 5PM, prior notice required.
  • Office hours will not be held unless at least one student requests them 24 hours in advance.
  • You can request office hours via email.
  • The link to the Zoom room for office hours will be posted on the Brightspace page.
• Department contact information: Please see https://hunter.cuny.edu/artsci/computer-science/contact/

If you need to contact me, please reach out via email. Please put “CSCI 355” in the subject to make it easier to find your emails.

Course description

• Course Description: This course provides an introduction to linear and integer linear programming, focusing on optimization techniques and their applications. Students will learn to formulate, analyze, and solve optimization problems using both theoretical and computational approaches.
• Learning Goals: By the end of the course, students will:
  • Develop the ability to formulate linear and integer linear programming models for optimization problems.
  • Gain a solid understanding of the theoretical foundations, including:
    • Algorithms for solving linear and integer linear programs.
    • Matrix and vector representations of linear and integer linear programs.
    • The importance of convexity in optimization and the expressive power of linear and integer linear programming.
  • Implement and solve linear and integer linear programming models using the OR-Tools Python library.

Course calendar

Relevant dates:

• 2026-01-26: Class canceled due to inclement weather
• 2026-01-28: First day of class for CSCI 35500
• 2026-02-16: No class
• 2026-03-11: Midterm exam
• 2026-04-01: No class (spring break)
• 2026-04-06: No class (spring break)
• 2026-04-08: No class (spring break)
• 2026-05-13: Last day of class for CSCI 35500
• 2026-05-20: Final exam (6:20-8:20 PM)

Assignment due dates will be posted on their respective pages.

For course meeting time and location, see the “Course information” section above.

This calendar may be out of date. For up-to-date information on academic dates see the Hunter website:

https://hunter.cuny.edu/students/registration/academic-calendar/

Course structure

Expected lecture topics (mostly in order):

• Linear algebra review
• Linear programming, modeling problems as LPs
• Using the OR-Tools Python module to solve optimization problems
• LP solving methods and their differences
• Integer programming, solving integer programs with branch and bound
• SAT reduction to ILP, demonstration of NP-completeness
• Modeling general discrete problems as ILPs
• Common ILP models, including the Traveling Salesman Problem
• Convex programming hierarchy

Lecture material is subject to change. Lectures may not align with classes.

There will be 2 homework assignments and 2 projects.

Grading

• Homework: 15%
• Projects: 15%
• Midterm exam: 30%
• Final exam: 40%

Per CUNY guidelines, this course uses the grading structure given here to map numerical course grades to letter grades: https://hunter.cuny.edu/students/registration/records-and-transcripts/grading-structure/