10926 Non-Linear Optimization Methods 1
Credits: 6 advanced credits in Industrial Engineering and Management or in Sciences - General
Prerequisites: 36 credits, including Differential and Integral Calculus I, Differential and Integral Calculus II, Deterministic Models in Operations Research. Students must also fulfill all English requirements and take bibliographic instruction in the Library.
Required: One of the following: Linear Algebra I, Mathematics for Students of Social Sciences, Linear Algebra for Natural Science Students
The course is based on Optimization: Foundations and Applications, by R.E. Miller (John Wiley & Sons, 2000), and on supplementary materials by Hagai Ilani that include the use of MS-Excel and GMAS demo software.
The course expands students’ knowledge on solving non-linear optimization problems. They learn to formulate various non-linear maximization and minimization problems and to select suitable tools for solving them. The course imparts a variety of definitions and methods for algebraic and numerical problem solving. The course presents the characteristics, convergence conditions, criteria for use, and more, for each method. Students apply their knowledge by solving problems in the area of industrial engineering and management in order to develop their ability to formulate various engineering problems and to select the appropriate methods for solving them.
Topics: Matrix algebra; Foundations: nonlinear methods – unconstrained maximization and minimization, constrained maximization and minimization; Iterative methods for nonlinear problems – solving nonlinear equations; solving unconstrained maximization and minimization problems; Constrained optimization in nonlinear models – nonlinear programming: fundamentals, duality and computational methods.
1Students may not write a seminar paper in the framework of this course.