The OR Society Undergraduate Award

One prize is awarded per registered institution per academic year. At each institution, the student who completes the best OR project as part of their relevant undergraduate degree course is awarded: 

  • A certificate
  • £50
  • The opportunity to present an overview of their project at The OR Society’s *Education and Research Seminar*
  • Each winning student’s name, their institution and course details, and the abstract of their project is published on The OR Society website
  • An article also features on The OR Society website and in Inside OR magazine with photographs of all prize winners at the seminar series or with photographs forwarded by the institutions

To request an application form for your institution, please email charlene.timewell [at]

Submission - Entries should be submitted by email unless infeasible. Please send entries to charlene.timewell [at]

Citations for The OR Society Undergraduate Award 2018

Jacob Curran-Sebastian, University of Manchester

After recently graduating from MMath Mathematics at the University of Manchester, Jacob is now preparing the work from his dissertation for publication. Besides this, he is applying for PhD positions with the intention to pursue a research career.

Lie algebraic methods for solving rime-inhomogeneous Markov chains

Markov chains appear in a wide range of contexts in mathematical biology, and have been considered, for example in epidemiology (House, 2012, 2015; Keeling & Ross, 2008) and in the modelling of ion channels (Epstein, Calderhead, Girolami, & Sivilotti, 2016; Colquhoun & Hawkes, 1981). In some cases, these processes have been assumed to be independent of time, largely for convenience. However, such assumptions need not be made, and indeed it is possible to derive a solution of the time-inhomogeneous system in cases where it is possible to exploit Lie algebraic methods to obtain matrix exponential solutions. Once these solutions have been obtained, there exist a number of numerical methods for approximating the resulting matrix exponentials (Moler & Van Loan, 2003; Higham, 2008), which can offer significant computational advantages over the standard methods for numerical integration.

Jacob Curran-Sebastian winner of 2018 Undergraduate Award with Peter Duck

Jacob Curran-Sebastian receiving his award from the Head of School, Peter Duck

Louisa James, University of South Wales

Following graduation from her BSc Mathematics course at the University of South Wales, Louisa is now applying for data analysis roles in industry linked to OR in Healthcare.

The University Timetabling problem

One common problem facing the higher education industry is that of obtaining a timetable of core events that satisfies both the students and staff in the work place as well as sustaining the policies and protocols of the establishment. This report aims to tackle this problem using a range of heuristic based methods and seeks to improve on the previous model at each stage of the analysis. T

he original problem is reduced by characterising constraints as hard and soft, and prioritising where necessary to allow for the utilisation of optimisation software. A procedure to solve this reduced problem is coded into the software to generate an optimal timetable solution. Introducing new factors and constraints into the problem and exploiting the available course data provided by the University of South Wales allows the construction of a more realistic solution. Modifying the original data set to produce a group of central events, while considering additional constraints representative of real world limitations enables the formation of a more accurate timetable.

Further improvements to the program using local search methods and evaluating the feasibility of the problem facilitates achievement of the optimum solution, scheduling all required sessions and accomplishing the original aim of the project. The report establishes additional aspects to be considered in the future to expand on the solutions, and eventually action the findings in practice.

Louisa James winner of 2018 Undergraduate Award with Penny Holborn

Dr Penny Holborn presenting the award to Louisa James

Hristo Dobrev, University of Leicester

Following graduation, Hristo is planning to set up his own business.  He believes that what he has learned in the operational research module of his BSc Mathematics course at the University of Leicester will be invaluable in providing him with a lot more ways to optimise any future business potential.

Risk Appetite

The aim of this project was to identify the optimal level of risk that Nottingham Credit Union should accept when making loans.

No loan is without risk, so if the credit union takes no risk it will make no loans and receive no loan interest.  However, if it takes too much risk, the bad debt will outweigh the interest received on loans that do repay.  It follows that between these two extremes there lies a level of risk that maximises net income (interest received less bad debt costs incurred).

There were two main parts to the project.  The first was to find a way to identify the level of risk associated with making any particular loan.  This was done analysing all the credit union’s loans made over the previous three years to identify the factors that increased or reduced, by using logistic regression.  The second part was to examine all loan applications received to identify the risk associated with each, using the regression model, and from this to calculate the expected net income at each level of risk. Logically, the credit union should make all loans on which the expected return is greater than zero so this gives the maximum level of acceptable risk and from this the average level of bad debt can be calculated.

The calculations need to be repeated for each level of interest rate charged by the credit union, as the interest rate affects the risk/reward balance for a loan.

All aspects of the project were successfully completed.  The results indicated that the credit union’s risk appetite was marginally too low, and that it should seek to improve its profitability by taking on marginally riskier loans than had previously been the case.

Hristo Dobrev winner of 2018 Undergraduate Award with Professor Jeremy Levesley

Hristo Dobrev receiving his award from Professor Jeremy Levesley

Sam Ball, University of Liverpool

After graduating from MMath Mathematics at the University of Liverpool, Sam plans to continue learning about OR through a PhD and carry this learning through to a career in consulting or management.

Integer Linear Programs

Integer Linear Programs (ILPs) are more complicated than Linear Programs over the rational numbers (LPs) since the Simplex algorithm (with quadratic average case complexity) can no longer be applied, and the ILP problem is known to be NP-complete. In this project we build on ideas from LPs to look at current methods of solution for ILPs. Whereas LPs have unique shadow prices, ILPs do not; they instead have dual price functions that only have to satisfy certain realistic constraints. It turns out that the structure of these dual price functions corresponds to the choice of solution algorithm. Our discussion of these results is largely based on the work of Wolsey [1]. We also discuss applications of this result, as well as recent developments and open problems in this area.

[1] L. A. Wolsey. Integer Programming Duality: Price Functions and Sensitivity Analysis. Mathematical Programming 20.1, 1980.

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