Introduction to Optimization

Catalog description

Modern study of linear programming with an emphasis on model formulation, solution, and interpretation of software output. Applications in work-scheduling, diet, capital budgeting, blending, production process, transportation, assignment, transshipment, and flow problems. Programming methods include the simplex method and its specialized variations, Big M Method, goal programming, and integer programming. Theoretical aspects include optimality conditions, sensitivity analysis, and duality. Requires using industry-standard software to strengthen the ideas and concepts. Cross-listed: MATH 480 and CS 480 are cross-listed. Students may not receive credit for both. Enrollment Requirement(s): for graduate students, MATH 264 or MATH 374 with a grade of C (2.0) or better. Prerequisite(s): for undergraduates, MATH 264 or MATH 374 with a grade of C (2.0) or better.