INTRODUCTION TO OPTIMIZATION

Prerequisites & course information

Requisites: ( COMP SCI 200 , 220 , 300 , or placement into COMP SCI 300 ) and ( MATH 320 , 340 , 341 , 345 , or 375 ) or graduate/professional standing Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Breadth - Natural Science Level - Intermediate L&S Credit - L&S Liberal Arts and Science Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Engage in topics about "optimization in practice". Audience: Both Grad & Undergrad 2. Use and analyze the results of state of the art optimization software. Audience: Both Grad & Undergrad 3. Implement and solve optimization problems using appropriate software tools. Audience: Both Grad & Undergrad 4. Design good models for realistic applications in engineering and the sciences. Audience: Both Grad & Undergrad 5. Develop a practical application of optimization technology. Audience: Both Grad & Undergrad 6. Independently formulate and solve optimization problems relevant to their field of study. Audience: Graduate Learning Outcomes: 1. Engage in topics about "optimization in practice". Audience: Both Grad & Undergrad 2. Use and analyze the results of state of the art optimization software. Audience: Both Grad & Undergrad 3. Implement and solve optimization problems using appropriate software tools. Audience: Both Grad & Undergrad 4. Design good models for realistic applications in engineering and the sciences. Audience: Both Grad & Undergrad 5. Develop a practical application of optimization technology. Audience: Both Grad & Undergrad 6. Independently formulate and solve optimization problems relevant to their field of study. Audience: Graduate