Our Knowledge Transfer Partnership with The University of Nottingham
Webroster Ltd is delighted to have now completed a Knowledge Transfer Partnership (KTP) with the University of Nottingham and supported by Innovate UK.
KTP’s are a nationwide programme to help innovative businesses benefit from the UK Knowledge Base by giving them access to knowledge, technology or skills at universities and other research organisations.
Home care providers are constantly required to juggle client care with business. This means that often, someone misses out and the result is that either clients receive poor or inconsistent care or providers are running inefficiently, spending more than they need to on care staff and mileage etc.
We decided that incorporating some advanced and innovative computer algorithms into our rostering software would enable us to provide our customers with this balance. The idea was to let the software do the work and make the decisions with minimal human intervention, whilst letting providers also retain as much control as possible.
The home care workforce optimisation problem is extremely complex and isn't getting easier; with life expectancy increasing, the management of this is becoming vastly comprehensive. We needed to give care providers a way to quickly and easily find the balance; to automatically produce a roster which truly optimises whatever area of the business they want to.
Dr. Dario Landa-Silva, Associate Professor in Computer Science at The University of Nottingham. Dario and the rest of the ‘Automated Scheduling, Optimisation and Planning’ research group had heard about our vision and thought there could be some common ground; they were looking for commercial, ‘real-world’ scenarios to help with their research and we were looking for highly specialised expertise to realise our idea.
Rodrigo Pinheiro, former artificial intelligence lecturer at the State University of Maringa, Brazil, was the KTP Research Associate on the project. His experience lies in combinatorial optimisation, including workforce scheduling and routing problems, travelling salesman problems and graph planarisation problems. He is in the final year of his Ph.D. studies within the Automated Scheduling and Planning Group at the University of Nottingham and is now employed at Webroster.
In addition to Rodrigo and Dario, two other students in the research group were involved in the project; Wasakorn’s focus is on mathematical solvers and Haneen’s focus is on evolutionary algorithms. Together, the group of academics used Webroster’s commercial evidence and real world situations to gather knowledge and solve the problem.
During the project eight research papers were produced as a result of the work, which have been published in leading academic journals and international conferences. The papers cover a range of research outcomes facilitated by this KTP project: Problem benchmark data sets from real-world scenarios (based on customer feedback) provided by Webroster; formal optimisation models for these benchmark problems; various optimisation algorithms including mathematical programming and tailored heuristics to produce high-quality solutions and application programming interface (API) to facilitate the implementation of the optimisation engine.
"This KTP project contributed enormously to the academic team’s research activity. The focus of this project, developing an optimisation engine to automate the generation of schedules for home healthcare workforce, is one of the key research interests of the academic team and their whole research group."
Dr Dario Landa-Silva, Associate Professor in Computer Science, The University of Nottingham
In April 2016, the KTP project came to a close and was awarded ‘Outstanding’ – the highest possible grade - by the KTP Grading Panel for meeting and exceeding its original objectives which were to improve homecare workforce utilisation by developing an adaptable software optimisation engine that solves any workforce management scenario that includes both rostering and routing.
The results of the KTP are beyond expectation. Webroster has gained significant knowledge, understanding and appreciation of optimisation problems and has been able to produce a unique solution to the problem. Added to this, the research profiles of the academic team have been strengthened in several aspects.
Having the three-way relationship was crucial to the success of the project; as a group, we achieved results that otherwise wouldn't be achievable. We extensively used the University access to academic journals and material on our research. Without this, we would not be able to obtain the algorithms we developed.