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 OR Challenge is organised by the School of Mathematics in partnership with an industry partner to be named later.
By participating in the challenge you will play the role of a consultant working with the industry partner who needs 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.
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.
The prizes will be anounced closer to the time but in previous years the prizes have included:
Each member of the winning team received a £400 prize and was offered a paid summer internship with the industry partner.
Each member of the runner-up team received a £300 prize.
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:
- Be interested in using numerate techniques to solve practical problems that enables decision makers to execute better decisions and make a difference
- Work individually or in a group of two.
- Be a Bachelor’s student enrolled in the last two years of the program at a UK University.
Registration information will become avalible in September 2023.
The School of Mathematics offers a number of MSc Programmes in Operational Research, using mathematical techniques to tackle real-life decision problems.
The main focus of the Optimization and Operational Research group is on mathematical and computing aspects of optimization. It has world-leading expertise in the solution of large sparse linear and quadratic problems by two of the core technologies in optimization - the simplex method and interior point methods. The group also has interests in nonlinear and global optimization, decomposition methods, parallel computing, industrial applications of optimization, and stochastic optimization. There is additional expertise in simulation and stochastic areas of operational research, and in the mathematics of energy systems.