Operations Research II

2018-2019
This course is offered in Dutch. Some of the descriptions may therefore only be available in Dutch.

Course Objective

To be introduced to the theory of stochastic processes and models that
are important in EOR practice. To learn modeling techniques for
translating an EOR problem into an appropriate stochastic model. To
learn how to apply optimization and simulation techniques for
performance analysis of stochastic systems.

Course Content

This is an introductory course in stochastic models. It builds upon the
basic course in probability theory and extends the theory of static
probability to dynamic stochastic processes. The course focuses on
Poisson process, discrete-time and continuous-time Markov chains, with
applications to queueing models, risk analysis, reliability problems,
and option pricing. It also discusses dynamic optimization and
stochastic simulation of these systems.

Teaching Methods

Combined lectures and tutorials.

Method of Assessment

1. Individual assignment. 2. Midterm exam. 3. Final exam.

Entry Requirements

Introductory courses on Probability Theory and Statistics

Literature

Hamdy A. Taha: Operations Research, An Introduction. Tenth Edition.
Pearson 2017.

Target Audience

Junior/Senior undergraduates in Applied Mathematics (e.g. Econometrics
and Operations Research)

Additional Information

The course is suitable to be taken in an exchange progam.

Recommended background knowledge

Courses in Mathematical Analysis, Discrete Mathematics, Linear Algebra.

General Information

Course Code E_EOR2_OR2
Credits 6 EC
Period P4+5
Course Level 200
Language of Tuition Dutch
Faculty School of Business and Economics
Course Coordinator dr. A.A.N. Ridder
Examiner dr. A.A.N. Ridder
Teaching Staff dr. A.A.N. Ridder
dr. D.A. van der Laan

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Study Group
Target audiences

This course is also available as: