CH E 469: Global Optimization

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Instructor:

Nick Sahinidis (nikos@uiuc.edu)

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Course Objectives:

To offer an in depth study of the general theory and methods of Global Optimization. We will study applications, algorithms, and software.

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Text:

Horst, Pardalos and Thoai: Introduction to Global Optimization, Kluwer, 1995.  Extensive additional material will be provided in class.

General Bibliography on Optimization
Bibliography on Deterministic Global Optimization

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Credit:

1 unit.  Course grade will be based on homework (20%), midterm (20%), take-home final exam (20%), paper presentation (20%), and computer project (20%).

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Topics covered: (each lecture: 80 minutes)

1. Introduction (1 lecture):
• Introduction
• Applications
• Course outline
2. Foundations (6 lectures):
• Convex/nonconvex sets and functions
• Local and global optimality conditions
• Algorithms, convergence and finiteness
• Computational complexity of global optimization
3. Global Optimization Methods (15 lectures):
• Cutting planes
• Outer approximation
• Convexification
• Decomposition
• Branch and Bound
• Lower bounding methods
• Branching techniques
• D.C. programming
• Lipschitzian programming
• Interval methods
• Range contraction
4. Special Topics (4 lectures):
• BARON
• Bilevel Programming
• Molecular structure prediction
• Global optimization on networks
• Semi-infinite programming
5. Project and paper presentations (3 lectures)

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