Knowledge Transfer Partnership

Computational Optimisation and Learning (COL) Lab

The Computational Optimisation and Learning (COL) Lab was launched in the summer of 2019 and is a group of academics, researchers and PhD students based in the School of Computer Science at the University of Nottingham. The COL was formed from a previously highly successful research group – the Automated Scheduling, Optimisation and Planning (ASAP) group. The ASAP existed for 22 years with a successful research track record in terms of PhD completions, publications, project funding and, most importantly, impact. The nature of the group changed over time with a gradual change towards optimisation and learning. With new academics and new funding, in 2019 it was decided to relaunch the group as the COL which better represents who they are and what they research. 

In collaboration with Webroster Ltd, a UK based software design company, researchers at the University of Nottingham developed Optimiser – a commercial software product using world-class artificial intelligence algorithms to schedule homecare workers. The software became a key component of Webroster.net’s offering contributing to its growth and in March 2020 Webroster Ltd was acquired by Access Group. At the same time, a new company, NDG Artificial Intelligence Ltd. (NDGAI), was established to focus on commercialisation of the Optimiser – renamed OptifAI®.

Rodrigo Pinheiro

One of the PhD students, Rodrigo Pinheiro, was employed in the KTP in collaboration with Webroster Ltd and became the Chief Optimisation Engineer in charge of the optimiser module within Webroster.net. During this intense period of research on optimisation methodologies for Workforce Scheduling and Routing Problems (WSRP), Dario Landa Silva and his team have developed optimisation models and intelligent algorithms to automatically generate schedules for a ‘mobile workforce’, i.e., workers that travel between locations to perform tasks.

Homecare is an example of this type of scenario, where nurses, social workers, carers etc. visit patients in their own homes to provide them with health and/or care services. Research revealed the computational difficulty of this type of problem and laid the foundation for the models and algorithms that followed.

Go to our About Us page and learn more about Rodrigo and his illustrious career including links to his published articles.

Dario Landa-Silva