PhD Studentship – Optimal Railway Network Maintenance

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Computer Science,Computer Science,Software Engineering,Engineering and Technology,Civil Engineering

Short info about job

Company: University of Nottingham

Department: Engineering

Hours: Full Time

Type / Role: PhD

Phone: +44-1206 8077667

Fax: +44-1252 7280883

E-mail: N\A


Detail information about job PhD Studentship – Optimal Railway Network Maintenance. Terms and conditions vacancy

Applications are invited for a PhD Studentship from suitably qualified graduates to work in the Resilience Engineering Research Group, at the University of Nottingham.

Project Description:

The UK railway comprises of 20,000 miles of track and over 40,000 bridges. Much of the infrastructure is aging and, in order to satisfy the future demand for passenger and freight transport, will experience increased traffic densities and loads. The maintenance of such systems, to ensure a safe and reliable service restricted by limited financial resources, is a significant challenge and needs to be carefully managed. Computer models are used to relate the future state of any asset (track, structures, signalling, electrification, communications etc) to the whole life costs when any maintenance strategy is adopted. To make best use of the financial resources available to maintain the railway network, decisions need to be made on a whole life, whole system basis. The assets feature dependencies between them such as common budgets, common possession time, common inspections and the ability to take advantage of opportunities where the condition of one asset provides the chance to carry out work on another. This produces large scales models and the objective of this project is to develop an optimisation framework to select the best maintenance and renewal strategies across the extensive asset base.

Through our Strategic Partnership with Network Rail, this project aims to develop an optimisation software to support the decision making to set the ‘best’ asset maintenance strategy. It is anticipated that the features of such a problem will need a methodology which exploits the features of the problem solved rather than using generic optimisation methods such as genetic algorithms. The optimisation strategy may use either single objective or multi-objective formulations along with appropriate constraints to ensure that a practical solution is achieved.


The funding available will cover the fees of a home / EU student, and a tax free stipend will be offered of £1,200 per month.


Informal enquiries may be addressed to Professor John Andrews, tel: 0115 84 68448 or Email: [email protected]

Please quote ref ENG1110 

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