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Applied Operations Research
Provider: Faculty of Science

Activity no.: 5554-19-07-31 
Enrollment deadline: 02/09/2019
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time02.09.2019, at: 09:00 - 10.11.2019, at: 16:00
Regular seats50
ECTS credits7.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserGiovanni Pantuso    E-mail address: gp@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 1
Scheme groupC
Exam formOral examination
Exam formOral examination, 30 minutes
Exam detailsThe 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 categoryHours
Lectures21.00
Practical exercises21.00
Project work60.00
Preparation103.00
Exam1.00
Sum206.00
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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