56:271 Nonlinear Programming Fall Semester 2003

This is a course in optimization, with emphasis on the theory, applications, and algorithms for nonlinear programming.

Topics:

• Convexity of sets and functions
• Solving systems of linear & nonlinear equations
• Unconstrained optimization algorithms
• Karush-Kuhn-Tucker optimality conditions
• Algorithms for optimization with constraints
• Lagrangian duality theory
• Quadratic programming
• Separable (piecewise-linear) programming
• Interior-point (path-following) methods
• Geometric Programming (posynomial & signomial)
• Nonconvex programming theory and algorithms

An introduction to the APL interactive computer language will be provided, primarily for defining objective and constraint functions for testing already-coded optimization algorithms. (No previous knowledge of this language is assumed.) LINGO will be used for optimization of some case studies.

A course in optimization, such as 56:171 Introduction to O.R., is a prerequisite. (In particular, students should be familiar with the simplex method for linear programming!)

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Last modified: 8 August 2003