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32934-01 - Vorlesung: Optimization and AI 3 KP

Semester Frühjahrsemester 2024
Angebotsmuster Jedes Frühjahrsem.
Dozierende Dietmar Maringer (dietmar.maringer@unibas.ch, BeurteilerIn)
Inhalt Many fields in business and economics involve optimisation. This course covers traditional (numerical) optimization methods, based on deterministic algorithms, such as gradient-based and gradient-free methods, or concepts from constraint-satisfaction. These mehods are highly efficient in some circumstances, but they also have their limits: They are no longer reliable when objective functions have more than one optimum, special constraints or requirements need to be satisfied, or the nature oft he problem is simply too complex. For these cases, meta-heuristics and artificial intelligence (AI) inspired concepts can be used. We will look into simple stochastic methods like Monte Carlo Search and Simulated Annealing/Threshold Accepting, but also into population based methods that mimic evolutionary processes or swarm intelligence.

To deepen the participants' understanding of these methods, their practical application, their strengths and limitations, the course is very much hands-on, allowing for numerous own 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 methods and concepts, and perform experiments. Participants are expected to have at least a basic knowledge of programming as taught in "58989 Computing for Business and Economics".
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Teilnahmebedingungen *) 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


Datum Zeit Raum
Freitag 01.03.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 08.03.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 15.03.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 22.03.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 29.03.2024 10.15-14.00 Uhr Ostern
Freitag 05.04.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Freitag 12.04.2024 10.15-14.00 Uhr Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Module 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)
Spezialisierungsmodul: Areas of Specialization in International and/or Monetary Economics (Masterstudium: International and Monetary Economics)
Leistungsüberprüfung Leistungsnachweis
Hinweise zur Leistungsüberprüfung Combination of active participation, assignment(s), and final exam.
written exam: 24.04.24; 08:30-09:30. WWZ S15: A-Z.
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 Leistungsüberprüfung Anm.: Belegen Lehrveranstaltung; Abm.: stornieren
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,1
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch
Anbietende Organisationseinheit Wirtschaftswissenschaftliche Fakultät / WWZ