Optimization (MATE6882)

Latest Course Syllabus-ABET Style () (PDF)

Credits: 3
Students should take this course at: 2nd Year - 1st Semester


This is a course on nonlinear optimization, both unconstrained and constrained. We will study optimality conditions and the basic numerical optimization methods with their convergence analysis. The numerical methods include: basic descent methods, conjugate direction methods, quasi Newton algorithms, reduced gradient method, gradient projection method, penalty and barrier methods, duality, and Lagrange methods. The material learned in this course is relevant to operation research, actuarial science, and mathematical modeling among others. An optimization problem is needed whenever one wants to optimize the performance of a system with the help of a mathematical model.