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 project abstract is published on The OR Society's website
  • An article also features in Inside OR magazine with photographs of all prize winners at the seminar series or with photographs forwarded by the institutions

Contact us

To request an application form, please contact us using the form opposite.

Please submit entries via the form opposite, unless unfeasible. If you are unable to do this, please contact the office and ask for Carol McLaughlin.

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Contact the Awards Panel

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Citations for The OR Society Undergraduate Award 2022

Manisha Gupta, University of Warwick

Following graduation from her degree in Mathematics, Operational Research, Economics and Statistics (MMORSE) Manisha will be joining the MSc Business Analytics programme at the University of Durham, followed by a CDT programme for implementing Operational Research and Statistical Techniques to solve business problems.


A business dashboard is an interactive and powerful analytics tool performing various functions such as heat maps, statistical analysis, data mining and predictive analysis. This
project implements Operational Research techniques to build a business dashboard for a pizza company called Birtelli’s. Analysis focuses on using the company data set to study
the customer behaviour and demographics. It also develops pricing models for the company by exploring different versions of the ε-greedy algorithm, the Iterative Least
Squares algorithm and Thompson Sampling. Comparison of these models are made based on achieving optimisation over an arbitrary number of plays. This project also develops
semantic analysis for customer reviews. Topic modelling is performed to quantify the relationship between the rating score and the qualitative text data by visualising text in a
high dimensional space. These tools are implemented in R and recommendations are made for assembling the tools into a dashboard.


Manisha Gupta - Undergraduate Award.jpg

Citations for The OR Society Undergraduate Award 2022

Mathew Cohn, Fraser Maclean, Benjamin Malcolm, Josh McKay, University of Strathclyde

The overall best dissertation from students at the University of Strathclyde was a group project by four students. Since graduating some of the students have secured graduate positions in banking and business analysis.  One student is working with a start-up business, whilst the other is taking some time to travel before applying for analysis / consulting roles. 


The problem domain of the investigation presented in this group dissertation is the applicability and adoption of Artificial Intelligence (AI) within an enterprise context. In particular, the research aims to provide business practitioners with an understanding of how to increase the likelihood of AI project successes. Additionally, given the relative recent emergence of the AI field, this research intends to map more of the less known AI territory. The research question surfaced after conducting the whole research: 

How do the factors influencing AI-related business decisions relate to one another?

A review of the literature related to AI adoption within a business context revealed that there is no one-size-fits-all method to successfully adopt AI, yet there are universal considerations that can help businesses make informed decisions around implementation. The intersection of the most pervasive AI challenges and common success characteristics highlight that a lack of commitment and attention to factors including data quality, AI strategy and organisational learning can lead to project failures. Moreover, the literature reviewed suggests that AI success stories frequently feature technology-embracing businesses that are enthusiastic about experimenting with AI in various contexts. However, many perceive the use of AI as experimental (and associate risk) and while certain aspects are, many of the core technologies have been around for several decades.

In an attempt to address the problems found in practice not covered by the literature, the research investigates the thoughts and opinions of expert practitioners from four sectors of interest concerning AI use. Semi-structured interviews with experts from sectors integral to modern societies were undertaken, namely the: (i) financial, (ii) legal, (iii) healthcare and (iv) manufacturing sectors.




Benjamin Malcolm, Fraser Maclean, Josh McKay and Matthew Cohn

Citations for The OR Society Undergraduate Award 2022

Sharon Ross, University of South Wales

Following graduation from her BSc degree in Mathematics, due 2023, Sharon plans to work as a Business Analyst.


The "knapsack problem" refers to the commonplace problem of packing the most valuable or useful items in a limited space with constraints without overloading the knapsack. The concept dates to the early works of Tobias Dantzig (2007).

This project investigates the application of the knapsack problem with regards to product distributions for businesses to optimise profit. Initially, various applications of the knapsack problems are described, ranging from its use in financial investment decisions, energy management and discount shopping strategies, the latter of which motivates the main goal of this investigation.

The theory that underpins the solution method is then developed. In particular, it is noted that requiring integer solutions necessitates the use of optimization software to efficiently answer larger scale practical problems.

The theory is subsequently applied to a bundling marketing strategy to create combinations of products in such a way as to maximise profits while adhering to limitations placed on the bundle, such as its size, weight, or value.

A subset of products sold by an online retailer that specialises in importing, exporting and distributing are selected to create a virtual store. These items are drawn from a range of product lines including “health & beauty”, “arts & crafts” and “back to school”. Information on item characteristics, such as individual cost, dimensions and weight, are entered on spreadsheets. These spreadsheets are exported into the optimization package Xpress where software tools are implemented in such a way that allows a non-specialist to use the program. Specifically, bundles of products that maximise the sale profit when the overall bundle dimension / weight is taken into consideration are produced.

The overall solution package combines the requirements of commerce and industry, (namely that the tools are simple and efficient to use and manage) with the rigour of advanced mathematical techniques (that is, the correct answers are produced). Specially, the easy-to-use front-end system allows easy management and updating of inventory items while the complex back-end system calculates the optimal solutions given the specified constraints.


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