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Awards - The Doctoral Award

The prize, for the "Most Distinguished Body of Research leading to the Award of a Doctorate in the field of O.R.", is an annual award, with the award being made at the OR Society’s Blackett Lecture in November.

The qualifying period is the calendar year in which the PhD or DPhil is defended or approved. For the full timetable, see the Guidelines tab. The thesis being submitted for consideration must have been examined at a UK University within the relevant time period.

With a prize fund of up to £2500 plus conference places available for the winner and runners-up, this represents an exciting development for PhD students.  Initial nominations are normally from the external examiner who has identified the body of research as of exceptional quality.

The winner of the award wins a cash prize of £1500. Up to two runners-up each receive £500. The winner has their name engraved on the George Paterson shield as a permanent record of their achievement.  The successful candidates are expected to present their work at the annual conference of the OR Society. A significant contribution towards to cost of the conference is available to all prize winners.

The deadline for receipt of submissions is 31st July. All submissions should be to Gavin Blackett, OR Society Secretary & General Manager (gavin.blackett@theorsociety.com).

The winner and runners-up for this award are announced in October.

Previous Winners

  • 2014
    Winner: Martin Takác,University of Edinburgh (citation available)
    Runners-up: Saeideh Nasiri, Lancaster University; Rob Shone, Cardiff University; Rui Wang, University of Sheffield
  • 2013
    Winner: T Lidbetter, London School of Economics (citation available)
    Runners-up: C Pickardt, University of Warwick; J Vile, Cardiff University
  • 2012
    Winner: Kabir Rustogi, University of Greenwich (citation available)
  • 2011
    Winner: Richard Wood, Cardiff University (citation available)
    Runners-up: S Allen, University of Nottingham; Dong Li, Lancaster University
  • 2010
    Winner: F Liberatore, University of Kent (citation available)
    Runners-up: Md Asaduzzaman, University of Westminster; G De Maere, University of Nottingham
  • 2009
    Winner: A Strauss, Lancaster University (citation available)
    Runners-up: S Adeyemi, University of Westminster; A Tako, University of Warwick
  • 2008
    Winner: K Kaparis, Lancaster University (citation available)
    Runner-up: D Arthur, University of Surrey

OR Society PhD prize winner for 2014

Randomized Coordinate Descent Methods for Big Data Optimization

Martin Takác’s thesis considers classes of problems in convex optimization that contain huge numbers of variables.  These optimization problems are applicable in machine learning and big data analysis, and hence are of great interest to operational researchers.

The thesis introduces new classes of randomized coordinate descent methods and analyses their performance in terms of providing tight bounds on the number of iterations the algorithm requires to obtain a solution with acceptable accuracy.  Parallel and distributed variants of the algorithms have been developed and tested on Hector and Archer, the largest supercomputers in the UK.  The practical importance of the research is demonstrated by the decision of Google and Amazon to implement two of the methods developed in the thesis.

Overall the thesis is substantial and advances the state-of-the-art significantly in the development of practical algorithms for an important class of convex optimization problems.  The external examiner commented that “Dr Takác is extremely on top of his game and has a deep intuition for the methods he developed” and “his breadth extends from deep theoretical analysis to competitive implementations”.  There are five papers resulting from the thesis, and the total of over 500 citations reported on Google Scholar provides ample evidence of the significant academic impact of the research.

OR Society PhD prize winner for 2013

Hide-and-Seek and Other Search Games

Thomas Lidbetter’s thesis is in the area of search games defined on networks.  The basic problem in this area is for a Searcher to select a path along which to travel at a constant speed to find a Hider who is immobile.  The Searcher aims to minimise the time to find the Hider, while the Hider chooses a point on the network that maximises this time.

Previous work in this area focuses on finding a single Hider or object.  However, the thesis introduces new models with multiple hidden objects, where the Searcher wants to minimise the time to find all of these objects.  This extension gives rise to new applications.  For example, the model has potential application to mine clearance, which resulted in Thomas Lidbetter giving an invited talk at the Geneva International Centre for Humanitarian Demining.  Another important contribution in the thesis is the introduction of the concept of expanding search, whereby the area searched expands at unit speed in a contiguous way rather than a Searcher moving at unit speed.  The problem of finding the best way to search for coal can be addressed by solving an expanding search game.

Overall the thesis is substantial and advances the state-of-the-art significantly in the theory of search games. The external examiner commented that “the thesis has made major contributions to the theory of search games”, “the level of originality is high” and “the mathematical analysis is elegant”.   There are seven papers resulting from the thesis, including five in high-quality journals, which provide ample evidence of the significant academic impact of the research.

OR Society PhD prize winner for 2012

Machine Scheduling with Changing Processing Times and Rate-Modifying Activities

Kabir Rustogi’s thesis is about scheduling with changing processing times and rate-modifying activities. Models that consider changing processing times are broadly classified into scheduling with deterioration and scheduling with learning. Scheduling with deterioration occurs when a machine slows down as more jobs are processed, while scheduling with learning occurs when a machine operator gains experience and therefore works faster as more jobs are processed. However, rate-modifying activities such as the maintenance of a machine, or a change of machine operator, can affect the deterioration or learning process. The thesis considers a variety of integrated models where both changing processing times and rate modifying activities are present. Moreover, a unified framework is introduced for tackling these integrated models, thereby adding coherence to an area of research where previous contributions were fragmentary.

The external examiner commented that the work is of high quality and significantly changes the frontier in machine scheduling with changing job processing times. The six high-quality journal publications resulting from the PhD, including an invited review in the European Journal of Operational Research and a paper in Operations Research, provide ample evidence of the significant academic impact of the research.

OR Society PhD prize winner for 2010

Citation for Federico Liberatore

Federico Liberatore accepting the award from Richard Eglese (right)

Supply systems are complex infrastructures devoted to the distribution of goods and services, composed by a combination of manufacturing, storage and transportation facilities.  Because of their complexity, supply systems are highly vulnerable to a variety of threats, such as natural disasters, intentional disruptions or accidental failures.  Federico’s dissertation, entitled ‘Protection Planning for Critical Infrastructure systems in Location Analysis: Models and Algorithms’, provides a comprehensive review and a categorization of previous design, interdiction, and protection modeling approaches. The second contribution of the thesis is to expand the protection literature by studying and solving new models and solution approaches that incorporate some realistic and complex features including uncertainty on the number of potential losses that a system may incur, capacity at the facility level, and correlated disruptions.

The external examiner commented, ‘Federico’s work shows great originality in both models development and solution methodologies.  In terms of models, the nominee has enriched the literature on protection models for supply systems by proposing original bilevel and stochastic models that incorporate the characteristics of complex supply systems in order to mitigate the impact of destructions or malfunctioning of critical infrastructures. Previous models in this area were based on some simplifying assumptions that strongly limited their practical applicability.  The new models introduced by Federico, although mathematically more complex, mirror in a more realistic way the functioning of real supply systems and the effects of possible disruptions.  Therefore they are much more realistic and can identify sounder protection plans than existent protection models.’

He also cited the fact that three chapters of Federico’s work had already been accepted for publication in international scholarly journals, saying ‘I believe this is a remarkable achievement for a PhD student.’

OR Society PhD prize winner for 2009

Citation for Arne Strauss

Arne Strauss accepting the award from Richard Eglese. In the background are A Tako (left) and S Adeyemi (right).

This PhD dissertation is devoted to Network Revenue Management (NRM). The author addresses a real world problem which is not well reported in existing literature, namely the impact of low-cost service providers on traditional providers. The typical example is the airline industry in which low-cost carriers such as Ryanair compete with traditional network carriers such as British Airways in some of the itineraries. The main salient point of low-cost providers is the fact that they only offer airline tickets without restrictions. Therefore, low cost providers aim at maximizing expected revenue too, but do not require market segmentation, which is one of the main pillars of the classical application of NRM used by traditional network carriers.

This PhD dissertation exhibited a deep knowledge of the relevant literature from both the academic and practitioner perspective.  The research uses state-of-the-art optimization techniques which were originally applied to the cutting stock problem and has been successfully applied to crew scheduling problems among others.  The strength of the dissertation is in the combination of appropriate mathematical tools, development of algorithms, and sound modelling of a very complex problem.  This research has a lot of potential for future developments and the author is developing an active research programme in collaboration with an industrial sponsor.

OR Society PhD prize winner for 2008

Citation for Konstantinos Kaparis

Konstantinos Kaparis accepting the award from Richard Eglese (right)

Konstantinos’ PhD dissertation is titled `Knapsack Problems: Inequalities, Separation and Heuristics'.  Many practical problems encountered by Operational Researchers can be formulated as zero-one linear programs (0-1 LPs). Such problems involve a sequence of `yes/no' decisions, represented by binary variables (i.e. variables which can only be equal to 0 or 1). The task is to maximise (or minimise) some suitable linear function of the decision variables, subject to various constraints. Examples of 0-1 LPs include capital budgeting problems (deciding in which projects to invest), facility location problems (selecting locations for the placement of one or more facilities), vehicle routing problems (determining the optimal route for one or more vehicles), scheduling problems (deciding which activities should begin in which time periods), and many others.

The external examiner felt that the work was original, providing new insights into both the zero-one knapsack problem and the multidimensional knapsack problem. This is attested to by aspects of the work done already being accepted for publication in two leading journals (European Journal of Operational Research and Mathematical Programming ).  Whilst being primarily of a theoretical nature, work such as this is often taken up by code developers for commercial optimisation software.

The judging panel was impressed by the plaudits received  and commented that ‘the thesis makes an important contribution to the already substantial literature on the zero-one knapsack and multi-dimensional problems’.