## Robert Weismantel: Catalogue data in Spring Semester 2019 |

Name | Prof. Dr. Robert Weismantel |

Field | Mathematics (Operations Research) |

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 | |
---|---|---|---|---|---|

401-3903-11L | Geometric Integer Programming | 6 credits | 2V + 1U | R. Weismantel, J. Paat, M. Schlöter | |

Abstract | Integer programming is the task of minimizing a linear function over all the integer points in a polyhedron. This lecture introduces the key concepts of an algorithmic theory for solving such problems. | ||||

Objective | The purpose of the lecture is to provide a geometric treatment of the theory of integer optimization. | ||||

Content | Key topics are: - lattice theory and the polynomial time solvability of integer optimization problems in fixed dimension, - the theory of integral generating sets and its connection to totally dual integral systems, - finite cutting plane algorithms based on lattices and integral generating sets. | ||||

Lecture notes | not available, blackboard presentation | ||||

Literature | Bertsimas, Weismantel: Optimization over Integers, Dynamic Ideas 2005. Schrijver: Theory of linear and integer programming, Wiley, 1986. | ||||

Prerequisites / Notice | "Mathematical Optimization" (401-3901-00L) | ||||

401-5900-00L | Optimization Seminar | 0 credits | 1K | R. Weismantel, R. Zenklusen | |

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

Objective | This lecture series introduces graduate students to ongoing research activities (including applications) in the domain of optimization. | ||||

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. |