School of Mathematics

Undergraduate Operational Research Challenge

Information concerning the Undergraduate Operational Research Challenge

Do you want to solve practical problems using mathematics?

The School of Mathematics at the University of Edinburgh invites you to participate in the Edinburgh Undergraduate Operational Research Challenge to design a solution for a practical problem using operational research.

What is Operational Research?

Operational Research is the mathematical science of helping decision makers to find better solutions for complex planning problems.

Operational research (OR) is used extensively in companies and in government to make better decisions. Its techniques are applied every day to problems in healthcare, transportation, energy, and many other areas. For example, OR was used during the Covid-19 pandemic to accelerate the development of vaccines. OR is also used to find the best ways to decarbonise our energy supplies and to design optimal radiation therapy treatments for cancer. These are only examples; the possible applications of OR are endless! This challenge is about applying OR to a real-world problem in portfolio optimization.

The Challenge!

The OR Challenge is organised by the School of Mathematics in partnership with Police Scotland.

By participating in the challenge you will play the role of a consultant working with Police scotland to derive a data-driven optimisation strategy for a real-world problem. 

The challenge consists of two phases. 

1) The development phase. 

After registering for the challenge, you will receive the detailed description of the task by email no later than the next business day.

You will also have access to short videos explaining mathematical concepts and tools that will help you carry out the task. 

At the end of this phase you should send to ORchallenge@ed.ac.uk the following documents: 

  • A pdf document of at most 10 pages, excluding appendices, with the detailed explanation of the approach you used, the computations performed, and the logical thinking supporting your recommendations, explaining the limitations of your modelling approach, and stating any caveats that apply to your results.
  • A second pdf document of 1 page that is a business report to be given to the client. You do not need to include any technical details in this report. The information needs to be convincing enough for the client to pick your solution.

The deadline for submission of the development phase has been extended to 23:59 17 January 2024. 

 2) The presentation phase. 

The highest ranked submissions from the development phase will be invited to give a live presentation of their work  to the decision-makers. 

Details of the specific date and place will be announced later.

​​​​Prizes

The prizes for the winning teams are as follows:

  • Each member of the winning team received a £400 prize and was offered a paid summer internship with Police Scotland*. 
  • Each member of the runner-up team received a £300 prize. 
  • Each member of the third place team recived a £50 prize.

*The paid internship may be subject to elibibility criteria.

Evaluation criteria

We are looking for 

  • An inventive and optimal solution.
  • A well-presented idea.
  • A detailed analysis. 
  • The correct use of optimization techniques and tools.
  • Appropriate visualisations such as charts, diagrams, panels, etc.
  • The overall approach adopted in terms of modelling and analysis.

The decisions of the judging panel are final and cannot be appealed.

To participate in this challenge you must:

  1. Be interested in using numerate techniques to solve practical problems that enables decision makers to execute better decisions and make a difference
  2. Work individually or in a group of two.
  3. Be a Bachelor’s student enrolled in the last two years of the program at a UK University.

Registration

Registrations open on the 2nd of October 2023. You can register using the following link. 

https://forms.office.com/e/33mqzxnrag

Registrations will close on the 23rd of October 2023 at 23:59.