NMAK19001U Applied Operations Research
MSc Programme in Mathematics-Economics
The course will introduce the students to practical aspects of Operations Research. The objective is to provide knowledge and skills necessary to work on Operations Research projects in practice.
It will go through the OR scientist "toolbox", that is, a minimal set of (mainly software) tools required for developing OR solutions.
The course will cover the following content:
- Using mathematical programming to model real-life decision problems: Given a description of a real-world optimization problem, the course will discuss how to formulate an appropriate mathematical programming problem and what are the issues involved in this phase
- Using state-of-the-art solvers to solve mathematical programming problems: Introduction to state-of-the-art optimization software (e.g., one or more among GAMS, Cplex, Gurobi, AMPL, or the like)
- Using general-purpose programming languages for interacting with solvers: Introduction to one or more general-purpose programming languages (e.g., Java, Python, C++) and their interface to state-of-the-art optimization software
- Implementation of advanced solution methods: Implementation of advanced solution methods for dealing with complicated mathematical programming problems
- Project work: From a description of a real-life problem formulate a suitable mathematical programming problem and solve the problem. Implementation of a solution method using selected optimization software.
At the end of the course the student should have:
- gained knowledge
- of common usage of continuous and integer variables for translating real-world decision problems into mathematical programming problems;
- of advanced solution methods for probles with complicated structures;
- acquired skills to:
- translate the description of real-life optimization problems to suitable mathematical programming problems;
- implement and solve mathematical programming problems using state-of-the-art optimization software such as GAMS, Cplex or the like;
- obtained the competences necessary to analyze and solve mathematical programming problems.
Academic qualifications equivalent to a BSc degree is recommended.
- Category
- Hours
- Exam
- 1
- Lectures
- 21
- Practical exercises
- 21
- Preparation
- 103
- Project work
- 60
- Total
- 206
Collective feedback on project work.
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 minutes30 minutes oral examination with 30 minutes preparation time.
- Exam registration requirements
The students must hand in two project reports that must be approved in order to qualify for the oral exam.
- Aid
- Only certain aids allowed
During the preparation time all written aid is allowed.
During the examination no written aid is allowed, except for a small written note with the outline of the presentation. - Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
- Re-exam
As the ordinary exam. If the projects were not approved before the ordinary exam they must be resubmitted. The projects must be approved at the latest three weeks before the beginning of the re-exam week.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- NMAK19001U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- C
- Course capacity
- No restrictions/ no limitation
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinators
- Giovanni Pantuso (gp@math.ku.dk)
- Trine Krogh Boomsma (trine@math.ku.dk)