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32934-01 - Vorlesung: Optimization and AI (3 KP)
| Semester | Frühjahrsemester 2025 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Dietmar Maringer (dietmar.maringer@unibas.ch, BeurteilerIn) |
| Inhalt | Many areas in business and economics involve optimization. This course covers "traditional" numerical optimization methods based on deterministic algorithms, including gradient-based and gradient-free methods, as well as concepts from constraint satisfaction. These methods are highly efficient in certain contexts. However, they also have limitations: they may be unreliable when objective functions have multiple optima, specific constraints or requirements must be met, or the problem is inherently complex. In such cases, meta-heuristics and AI-inspired techniques can be employed. We will explore simple stochastic methods like Monte Carlo Search and Simulated Annealing/Threshold Accepting, as well as population-based methods that mimic evolutionary processes or swarm intelligence, like Genetic Algoritms, Differential Evolution, or Particle Swarm Optimization. To deepen participants' understanding of these methods, their practical applications, strengths, and limitations, the course is highly hands-on, providing ample opportunities for individual implementations and experiments. |
| Lernziele | Successful participants should be familiar with numerical and computational methods for simple and demanding optimization problems. Also, they will improve their programming skills with special emphasis on the implementation of economic / management models and related methods. |
| Literatur | Lecture material will be provided. There is no designated textbook, but to get a flavor of the topics or to deepen their knowledge, (prospective) participants might find the following books (in alphabetical order) helpful: *) Gilli, M.; Maringer, D. & Schumann, E. Numerical Methods and Optimization in Finance, Academic Press, 2nd edition 2019. (or 1st ed., 2011) *) Michalewicz, Z. & Fogel, D. B. How to Solve It: Modern Heuristics, Springer, 2005 *) Brabazon, A.; O'Neill, M. & McGarraghy, S. Natural Computing Algorithms, Springer, 2015 *) Hillier, F. & Liebermann, G., Introduction to Operations Research, McGraw-Hill, 11th ed., 2019. *) Miranda, M. J. & Fackler, P. L. Applied Computational Economics and Finance The MIT Press, 2002 *) Brandimarte, P. Numerical Methods in Finance and Economics, Wiley-Interscience, 2006 Specific recommendations and additional literature to be announced during the course. how these can be setup, implemented, and analysed. |
| Bemerkungen | Throughout the course, we will use Python to implement various methods and concepts, as well as to conduct experiments. Participants are expected to have a basic knowledge of Python programming, at least to the level taught in "58989 Computing for Business and Economics." |
| Weblink | Weblink |
| Teilnahmevoraussetzungen | *) 58989 Computing for Business and Economics (or equivalent) |
| Anmeldung zur Lehrveranstaltung | Registration: Please enroll in the Online Services (services.unibas.ch); Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html After successful registration you can enroll for the course in the Online Services (services.unibas.ch). Applies to everyone: Enrolment = Registration for the course and the exam! |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Freitag | 10.15-14.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Freitag 21.02.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Freitag 28.02.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Freitag 07.03.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Freitag 14.03.2025 | 10.15-14.00 Uhr | Fasnachstferien |
| Freitag 21.03.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Freitag 28.03.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Freitag 04.04.2025 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Module |
Kernmodul: Core Areas in Monetary Economics (Masterstudium: International and Monetary Economics) Modul: Field Electives in Economics and Public Policy (Masterstudium: Economics and Public Policy) Modul: Risiko-Analyse (Masterstudium: Actuarial Science) Modul: Specific Electives in Data Science and Computational Economics (Masterstudium: Wirtschaftswissenschaften) Modul: Technology Field (Masterstudium: Business and Technology) Modul: Vorbereitung Masterarbeit Wirtschaftswissenschaften (Masterstudium: Sustainable Development) |
| Prüfung | Leistungsnachweis |
| Hinweise zur Prüfung | Combination of active participation, assignment(s), and final exam. written exam: date and room tbd Late deregistration is not possible for this course. If you do not wish to take part in the exam, please cancel your registration within the registration deadline. |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |