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 Sopra Steria.
By participating in the challenge you can play the role of a consultant working at Sopra Steria who needs to derive a data-driven optimisation strategy for a consultancy business who needs to determine the optimal allocation of consultants to projects.
From an Operational Research perspective, this is an optimization problem consisting of finding the optimal trade-off between maximising the profits obtained from completing projects while ensuring that a set of customer requirements are satisfied.
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 portfolio.
The Deadline for the development phase submissions is 10 January 2023.
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
Each member of the winning team will receive a £400 prize and will be offered a paid summer internship at Sopra Steria.
Each member of the runner-up teams will receive a £300 prize.
Sopra Steria, a European Tech leader recognised for its consulting, digital services and software development, helps its clients drive their digital transformation to obtain tangible and sustainable benefits. It provides end-to-end solutions to make large companies and organisations more competitive by combining in-depth knowledge of a wide range of business sectors and innovative technologies with a fully collaborative approach. Sopra Steria places people at the heart of everything it does and is committed to making the most of digital technology to build a positive future for its clients. With 47,000 employees in nearly 30 countries, the Group generated revenue of €4.7 billion in 2021.
We’re a people business, and we’re incredibly proud of the people who make Sopra Steria one of the UK Best Workplaces in the "Great Place to Work UK" Super Large category.
Furthermore, we are proud that "Great Place to Work" has ranked Sopra Steria Group 8th on the Best Workplaces in Europe list! https://www.greatplacetowork.co.uk/awards/europes-best-workplaces/2022/multinational/ The global benchmark for employee experience acknowledges the Group's efforts in rolling out a responsible employer strategy based on a long-term vision and recognises its caring and inspiring culture. Sopra Steria is committed to providing an attractive working environment and supporting its employees in their professional development.
Our Analytics & Automation Practice within Sopra Steria's Private Sector UK division has established a strong and sustainable relationship with the School of Mathematics at The University of Edinburgh, having successfully completed numerous collaborative projects, including several MSc level dissertations, practical courses and challenges in the field of Data Analytics & Data Science.
Company's Website:
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:
- 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
Please register by following the misrosoft forms link
https://forms.office.com/r/cKsKUh5msp
If you will work in a group of two, include also the information of your partner in your registration.
The deadline for registration is at 23:59 on 24 October 2022.
Your registration will be acknowledged the next business day.
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.