Robert Weismantel: Catalogue data in Autumn Semester 2018 |
| Name | Prof. Dr. Robert Weismantel |
| Field | 27 |
| Address | Institut für Operations Research ETH Zürich, HG G 21.5 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 48 15 |
| robert.weismantel@ifor.math.ethz.ch | |
| URL | https://math.ethz.ch/ifor/groups/weismantel_group/robert-weismantel.html |
| Department | Mathematics |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 401-3901-00L | Mathematical Optimization  | 11 credits | 4V + 2U | R. Weismantel | |
| Abstract | Mathematical treatment of diverse optimization techniques. | ||||
| Learning objective | Advanced optimization theory and algorithms. | ||||
| Content | 1) Linear optimization: The geometry of linear programming, the simplex method for solving linear programming problems, Farkas' Lemma and infeasibility certificates, duality theory of linear programming. 2) Nonlinear optimization: Lagrange relaxation techniques, Newton method and gradient schemes for convex optimization. 3) Integer optimization: Ties between linear and integer optimization, total unimodularity, complexity theory, cutting plane theory. 4) Combinatorial optimization: Network flow problems, structural results and algorithms for matroids, matchings, and, more generally, independence systems. | ||||
| Literature | 1) D. Bertsimas & R. Weismantel, "Optimization over Integers". Dynamic Ideas, 2005. 2) A. Schrijver, "Theory of Linear and Integer Programming". John Wiley, 1986. 3) D. Bertsimas & J.N. Tsitsiklis, "Introduction to Linear Optimization". Athena Scientific, 1997. 4) Y. Nesterov, "Introductory Lectures on Convex Optimization: a Basic Course". Kluwer Academic Publishers, 2003. 5) C.H. Papadimitriou, "Combinatorial Optimization". Prentice-Hall Inc., 1982. | ||||
| Prerequisites / Notice | Linear algebra. | ||||
| 401-5900-00L | Optimization Seminar | 0 credits | 1K | R. Weismantel, R. Zenklusen | |
| Abstract | Lectures on current topics in optimization | ||||
| Learning objective | Expose graduate students to ongoing research acitivites (including applications) in the domain of otimization. | ||||
| Content | This seminar is a forum for researchers interested in optimization theory and its applications. Speakers are expected to stimulate discussions on theoretical and applied aspects of optimization and related subjects. The focus is on efficient algorithms for continuous and discrete optimization problems, complexity analysis of algorithms and associated decision problems, approximation algorithms, mathematical modeling and solution procedures for real-world optimization problems in science, engineering, industries, public sectors etc. | ||||