Data-driven Decision Making in Operations Research

6 EC

Semester 2, period 4, 5

5334DDDM6Y

Owner Master Mathematics
Coordinator dr. A.V. den Boer
Part of Master Mathematics, specialization Algebra and Geometry, year 1Master Mathematics, specialization Analysis and Dynamical Systems, year 1Master Mathematics, specialization Mathematical Physics, year 1Master Mathematics, specialization Stochastics , year 1Master Mathematics, specialization Stochastics , year 1Master Stochastics and Financial Mathematics, specialization Data Analysis and Statistics, year 1Master Stochastics and Financial Mathematics, specialization Financial Mathematics, year 1Master Stochastics and Financial Mathematics, specialisation Probability and Decision Making, year 1Master Mathematics, specialisation Discrete Mathematics and Quantum Information, year 1

Course manual 2025/2026

Course content

Course goal: The goal of this course is to gain working knowledge of standard concepts and techniques in multi-armed bandit theory and to be familiar with typical applications in operations research.

Description: In this course we will study data-driven decision problems: optimization problems for which the objective function (i.e. the relation between decision and outcome) is unknown upfront, and has to be learned from accumulating data. These problems have an intrinsic tension between statistical goals and optimization goals: learning how the system behaves (the statistical goal) is accelerated by experimenting with different actions, while for taking good decisions (the optimization goal), one would like to limit experimentation and use estimated optimal decisions. We will study this `exploration-exploitation' trade-off for so-called `multi-armed bandit problems', the paradigmatic framework for dynamic optimization problems with incomplete information. We will discuss standard building blocks of the state-of-the-art theory, and we will discuss applications such as dynamic pricing and assortment optimization problems.

Objectives

  • The goal of this course is to gain working knowledge of all the standard concepts and techniques in multi-armed bandit theory, and to be familiar with typical applications. 

Teaching methods

  • Presentation/symposium
  • Lecture
  • Self-study

Learning activities

Activity

Hours

Hoorcollege

28

Tentamen

3

Self study

137

Total

168

(6 EC x 28 uur)

Attendance

This programme does not have requirements concerning attendance (TER-B).

Assessment

Item and weight Details

Final grade

1 (100%)

Deeltoets

The method of assessment is to be decided, but will probably be a mix of: giving (2) presentations and an oral exam.

Assignments

The final grade is determined based on home work assignments (if any) and an exam (oral or written, depending on # students), and possibly on presentations + written report on research paper(s) (again depending on # students).More details will be communicated via Canvas

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

WeeknummerOnderwerpenStudiestof
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

Contact information

Coordinator

  • dr. A.V. den Boer