This is an excellent opportunity to put abstract algorithm design, combinatorial optimisation, heuristics and evolutionary algorithms, software engineering and systems modelling skills into practice on a critically important real-world problem of routing and logistics.

Applications are invited for a student to work on a research project in Combinatorial Optimisation for “Virtual Fleet” Logistics. The project is sponsored by Transfaction Ltd and supervised by Professor Peter Cowling at the University of York, one of the UK's elite Russell group of research-intensive universities set in a beautiful, historic city. The project is fully funded paying fees plus a tax-free stipend of £16,746 p.a. The student will study for an Engineering Doctorate in Large Scale Complex IT Systems at the University of York. The EngD is a full time, 4-year doctoral level research degree involving both taught and research components. 

The Research Project: 
Road transport logistics is essential to the UK and worldwide economy, while also being a major contributor to CO2 emissions. Logistics companies with large fleets of vehicles are able to combine pick up and delivery requests from a range of customers to minimise delivery costs. Medium-sized and small logistics companies (with a turnover below £20m) receive work in an uncoordinated manner and the result is inefficient running and unladen miles. Transfaction has a unique methodology, based on decades of industry experience, for consolidating and managing the work of medium-sized and small logistics companies to create a large “virtual fleet” so that everyone benefits, and CO2 emissions are reduced through reductions in unladen miles.

In this project we will investigate combinatorial optimisation approaches for planning and routing of this “virtual fleet”. The main phases are outlined below:
- Read background literature (particularly on routing problems such as the Travelling Salesman Problem (TSP), the Pick-up and Delivery Problems with Time Windows (PDPTW) and the Vehicle Routing Problem with Time Windows (VRPTW)). 
- Discuss with Transfaction (and potentially its clients) to understand the precise nature of the business problems.
- Create a simulation environment to generate problem instances
- Write software capable of reading in real-world data and placing it in the format of the simulation environment.
- Model the problem of maximising efficiency and minimising CO2 emissions as a problem of combinatorial optimisation.
- Design heuristics (e.g. using Local Search, Variable Neighbourhood Search, Simulated Annealing, Monte Carlo Tree Search and Hyperheuristics) capable of providing high-quality plans to modelled problems in acceptable CPU time.
- Investigate mixed-initiative approaches which combine human expertise and computer power in the planning process.
- Conduct wide-ranging experiments for real and simulated problems to investigate the effectiveness of the approaches developed.

There are significant opportunities for publication during this project and for commercialisation of the work.

Peter Cowling has over 20 years experience in developing models and optimisation heuristics/algorithms for complex, real-world planning, scheduling, routing and optimisation problems. Of particular relevance to this project is experience in mobile workforce planning (two recent projects with Trimble MRM Ltd.) and experience in asset management using unprecedentedly detailed data (two current projects with Gaist Ltd.). 

The sponsoring organisation Transfaction (www.transfaction.com) is a company which passionately believes it is possible to reduce the harmful impact of road transport and logistics on our environment.  The company believes that sustainability is synonymous with best business. Transfaction works with a range of leading companies to assist them in achieving their sustainability goals and to improve their profitability. 

Entry Requirements, Funding and Applications 
Applicants should be highly motivated and have a minimum of an upper second class honours degree in Computer Science or related discipline (e.g. Maths with Computing, Electrical Engineering, operational Research). Significant programming experience, practical knowledge of AI techniques, and modelling expertise are essential. Knowledge of decision support, OR and geospatial information technologies is helpful. Applicants who have specialised in artificial intelligence or operational research (e.g. at Masters level) are particularly welcome to apply.

The successful applicant will receive fees and a tax-free stipend from the 
Engineering and Physical Sciences Council (EPSRC) of £16,746 p.a.  Please note there are eligibility requirements – see:- http://www.epsrc.ac.uk/funding/students/pages/eligibility.aspx
For further information on the EngD and how to apply for this position please visit www.cs.york.ac.uk/engd/. Informal enquiries can be made to Mrs Dawn Forrester ([log in to unmask]).