Introduction to optimization problems and algorithms emphasizing problem formulation, basic methodologies, and underlying mathematical structures. Classical optimization theory focusing primarily on linear optimization as well as recent advances in the field. Topics include modeling issues and formulations, linear programming and its duality theory, sensitivity analysis, large-scale optimization, integer programming, introduction to non-linear optimization, interior-point methods, and network optimization problems Applications considered include production planning, resource allocation, network routing, transportation, fleet management, graph problems, and problems from finance and computational biology. Meets with ENG SE 524 but requires more advanced problem sets and exams. Students may not receive credit for both. 4 cr.