OPERATIONS RESEARCH-DETERMINISTIC MODELING

Prerequisites & course information

Requisites: MATH 222 and ( MATH 340 , 341 , 345 or 375 ), or member of Engineering Guest Students Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Write an algebraic formulation of an optimization model that captures the main decision elements of practical problems Audience: Undergraduate 2. Use an algebraic modeling language to solve an optimization model Audience: Undergraduate 3. Recognize network structures and model operations research problems using them Audience: Undergraduate 4. Model logical constraints using binary decision variables Audience: Undergraduate 5. Demonstrate understanding of the basic ideas behind algorithms for solving linear programming and discrete optimization problems Audience: Undergraduate 6. Demonstrate understanding of the impact of convexity on an optimization instance’s complexity Audience: Undergraduate Learning Outcomes: 1. Write an algebraic formulation of an optimization model that captures the main decision elements of practical problems Audience: Undergraduate 2. Use an algebraic modeling language to solve an optimization model Audience: Undergraduate 3. Recognize network structures and model operations research problems using them Audience: Undergraduate 4. Model logical constraints using binary decision variables Audience: Undergraduate 5. Demonstrate understanding of the basic ideas behind algorithms for solving linear programming and discrete optimization problems Audience: Undergraduate 6. Demonstrate understanding of the impact of convexity on an optimization instance’s complexity Audience: Undergraduate