80% our impact in mathematical sciences recognised as very considerable in reach and significance


The University of Portsmouth submitted a new unit to the REF 2014 Panel 10 Mathematical Sciences, comprising work from two main research clusters: Nonlinear and Complex Systems, and Logistics and Operational Research. The work spanned the spectrum from theoretical advances in these subjects, through to applications addressing specific challenges in collaboration with academic and industrial partners. Eleven staff were submitted by the University of Portsmouth. The submission included two impact case studies illustrating our impact on healthcare logistics and the management of financial risk.

  • 9.8% of our research outputs were rated world-leading (4*) and 61% either world-leading (4*) or internationally excellent (3*)
  • 80% of our impact was rated as having very considerable reach and significance (3*)
  • Out of 53 institutions across the UK submitting in this Unit we were ranked 24th for impact at world-leading (4*) and internationally excellent (3*) level, and ranked joint 1st among post-1992 universities
  • 62% of our submission overall was rated as world-leading or internationally excellent
  • Among post-1992 universities, we were ranked 2nd for overall performance

Research groups / Research themes

Operational research (in the logistics and operational research group)

The work of the Logistics and Operational Research Group (LORG) is focussed on mathematical aspects of Operational Research (OR) with strengths including the theory underlying multi-objective optimisation, polynomial optimisation, and combinatorial optimisation. Fundamental research in these areas also leads to the development of more realistic and flexible methodologies and algorithms that can be applied to solve problems in situations arising in the healthcare, logistics, and renewable energy sectors, and the group has also engaged in impact-generating activities in these areas. 

Applied Mathematics (in the nonlinear and complex systems group)

The main academic aims of the group are in Nonlinear Dynamics and its applications, including the development of algebraic techniques for determining integrability (n-body type problems and others), algebraic techniques for the analysis of chemical and biochemical reaction networks (finding specific criteria concerning the structure of a network, and qualitative information about its parameters, that restrict the qualitative behaviour). We seek novel methods for construction and analysis of trajectories (Orbital Mechanics of solar sails), criteria for (and construction and analysis of) dynamical systems that exhibit directed transport and collective phenomena (with applications to energy transfer in biomolecules and others), and the use of statistical mechanics to analyse geological hazards (e.g., improved models for landslide distributions, matching real-world data).

Impact case studies

The use of goal programming to optimise resource allocation in hospitals in the UK and China

Managers of hospital units are required to allocate medical resources in accordance with, sometimes conflicting, objectives and performance targets and against continual variations in patient flow, staff and bed availability. The Logistics and Operational Research Group (LORG) at the University of Portsmouth has developed novel models, based on a combination of discrete event simulation, multi-phase queuing theory, and goal programming, that have improved the understanding of ward logistics by hospital managers in the UK and China, enabling them to make changes that have improved the efficiency of bed allocation, patient flow and allocation of medical resources and improved outcomes for patients.

Use of goal programming models to assist strategic financial investment decision making

This statement details the impact of research undertaken by members of the Logistics and Operational Research Group (LORG) at the University of Portsmouth in the area of strategic financial investment portfolio selection. A set of goal programming models was developed, which for the first time allowed the investment fund managers to consider a wider range of objectives beyond the usual risk and return paradigm. As a result, the decision making capabilities of key investment fund managers and advisors including those working for the Kuwait Sovereign Wealth Fund were enhanced, resulting in improved decision making capabilities.

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