The interaction of data science (DS) and optimisation (O) is the central theme of the working group (DSO). DSO originates from the observation that, on the one hand, real time optimisation algorithms are tightly linked to the data-context, and on the other hand, many data-analytic algorithms rely on optimisation algorithms, while many modern optimisation algorithms have some form of machine learning embedded. The first observation has a.o. led to developments in automated algorithm tuning, configuration and construction to adapt or even create algorithms from a historical body of data. The second observation is cause to development of similar ideas in different contexts but without much interaction. It is the aim of the working group to bring the two domains closer to each to better contribute to the aims of EURO, the European Organisation for Operations Research.
Deadline for submission of full papers: 10 March 2017 ( well after notification for acceptance at CEC and CPAIOR)
Notification of acceptance: 10 April 2017
Workshop date: 5 June, 2017