Faculty of Science

Applied Operations Research
Provider: Faculty of Science

Activity no.: 5554-19-07-31
	Enrollment deadline: 02/09/2019

Place

Department of Mathematical Sciences

Date and time

02.09.2019, at: 09:00 - 10.11.2019, at: 16:00

Regular seats

ECTS credits

7.50

Contact person

Nina Weisse E-mail address: weisse@math.ku.dk

Enrolment Handling/Course Organiser

Giovanni Pantuso E-mail address: gp@math.ku.dk

Written language

English

Teaching language

English

Semester/Block

Block 1

Scheme group

Exam form

Oral examination

Exam form

Oral examination, 30 minutes

Exam details

The students must hand in two project reports that must be approved in order to qualify for the oral exam. Only certain aids allowed. During the preparation time all written aid is allowed.

Course workload

Course workload category	Hours
Lectures	21.00
Practical exercises	21.00
Project work	60.00
Preparation	103.00
Exam	1.00

Sum	206.00

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.

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.

Literature

See Absalon

Teaching and learning methods

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

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