## David Adjiashvili: Catalogue data in Autumn Semester 2022 |

Name | Dr. David Adjiashvili |

Address | Institut für Operations Research ETH Zürich, HG G 21.3 Rämistrasse 101 8092 Zürich SWITZERLAND |

david.adjiashvili@ifor.math.ethz.ch | |

Department | Mathematics |

Relationship | Lecturer |

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

401-0053-00L | Discrete Mathematics | 4 credits | 2V + 1U | D. Adjiashvili | |

Abstract | Introduction to foundations of discrete mathematics: combinatorics (elementary counting), graph theory, algebra, and applications thereof. | ||||

Objective | The main goal is to get a good understanding of some of the most prominent areas within discrete mathematics. | ||||

401-0647-00L | Introduction to Mathematical Optimization | 5 credits | 2V + 1U | D. Adjiashvili | |

Abstract | Introduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering. | ||||

Objective | The goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering. | ||||

Content | Topics covered in this course include: - Linear programming (simplex method, duality theory, shadow prices, ...). - Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...). - Modelling with mathematical optimization: applications of mathematical programming in engineering. | ||||

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. Compared to "Mathematical Optimization", this course has a stronger focus on modeling and applications. |