Applied Operations Research

Course content

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.
Education

MSc Programme in Mathematics-Economics

 

Learning outcome

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.

3 hours of lectures and 3 hours of exercises per week for 7 weeks. In addition to this, individual project work.

Operations Research 1 (OR1) or similar is strongly recommended. It is also advised, but not necessary, to take this course before other advanced Operations Research courses.

Academic qualifications equivalent to a BSc degree is recommended.

Collective feedback on project work.

ECTS
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
30 minutes oral examination with 30 minutes preparation time.
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.
Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 21
  • Practical exercises
  • 21
  • Project work
  • 60
  • Preparation
  • 103
  • Exam
  • 1
  • English
  • 206

Kursusinformation

Language
English
Course number
NMAK19001U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Schedulegroup
C
Capacity
No restrictions/ no limitation
Studyboard
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinators
  • Giovanni Pantuso   (2-767f4f7c7083773d7a843d737a)
  • Trine Krogh Boomsma   (5-78766d7269447165786c326f7932686f)
Saved on the 12-06-2019

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