# Rico Zenklusen: Catalogue data in Autumn Semester 2014

Name | Prof. Dr. Rico Zenklusen |

Field | Mathematics |

Address | Institut für Operations Research ETH Zürich, HG G 22.4 Rämistrasse 101 8092 Zürich SWITZERLAND |

Telephone | +41 44 633 93 42 |

rico.zenklusen@ifor.math.ethz.ch | |

URL | https://www.math.ethz.ch/ifor/people/rico-zenklusen.html |

Department | Mathematics |

Relationship | Assistant Professor |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

401-0647-00L | Introduction to Mathematical Optimization | 5 credits | 2V + 1U | U.‑U. Haus, R. Zenklusen | |

Abstract | Introduction to basic techniques and problems of mathematical optimization. | ||||

Objective | The goal is to get a good understanding of some of the most important mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. | ||||

Content | Topics covered in this course include: - Linear programming (simplex method, duality theory, shadow prices, ...). - Basic combinatorial optimization problems (spanning trees, network flows, knapsack problem, ...). | ||||

Literature | Information about relevant literature will be given in the lecture. | ||||

Prerequisites / Notice | This course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics and more. | ||||

401-5900-00L | Optimization and Applications | 0 credits | 1K | R. Weismantel, B. Gärtner, D. Klatte, J. Lygeros, M. Morari, K. Schmedders, R. Smith, R. Zenklusen | |

Abstract | Lectures on current topics in optimization | ||||

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, invited from both academic and non-academic institutions, are expected to stimulate discussions on theoretical and applied aspects of optimization and related subjects. The focus is on efficient (or practical) 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. |