The D3EMO Modeling Week on Data Driven Decision Making and Optimization took place on 3rd-7th September 2018 at the Copenhagen Business School (CBS) in Copenhagen, Denmark
It was organised by
– Prof. Dolores Romero Morales, Professor of Operations Research, Copenhagen Business School, Department of Economics
– Prof. Emilio J. Carrizosa Priego, Professor of Statistics and Operations Research, University of Seville, Department of Statistics and Operations Research
Problems were presented by
- AirFrance (Augustine Lombard)
- Central Bureau voor de Statistiek (Marc Ponsen)
- DSB (Natalia Rezanova)
- TESCO (Eleanor Evans and Matthew Fryett)
PhD, PostDoc and researchers from all over the world (Belgium, Denmark, Greece, Italy, Poland, Spain, UK, Vietnam, etc.) attended this modelling week.
On Monday 3rd, after the welcome given by organizers, two companies (TESCO and CBS) presented their problems and the seventeen participants were divided into two groups, one for each problem; we had time until Tuesday evening to study the problem and propose some solution methods. On Wednesday 5th the other two companies (DSB and AirFrance) introduced their two problems and two new groups were formed, which worked together until Thursday evening. 
Companies’ problems can be classified into two macro-category: dealing with a lot of data (forecasting and visualization) and reasoning about the abstract problem (modeling).
During Friday, the last day of the Modeling Week, every group exposed its results, through an oral presentation and some slides; DSB representatives were present. Moreover, also some trainees talked briefly about their research topics. The study group ended in the early afternoon.
All groups analysed deeply the companies’ problems and produced written reports or slides, which will be delivered to the companies. In particular:
– The TESCO group tried to replicate the company model to forecast the customer daily demand for each product and store of the firm; they implemented some forecasting models after analysing the dataset through queries and statistical methods;
– The CBS group studied the dataset about air pollution and proposed methods to visualize data in order to have more sociological impact;
– The DSB group modelled the problem of scheduling cleaning operations of trains in the same way of the company (except for some simplifications), they developed their own instances and also suggested other models and ideas to tackle the problem;
– The AirFrance group tried to model the planning of aircrafts but had to deal with constraints very difficult to describe mathematically.
Another main outcome the whole modelling week produced was making all of us trainees bond with each other, creating connections that will last in the years to come, as well in other conferences or PhD schools. It was also great and inspiring to see companies really interested to collaborate with universities and research centres, giving us the chance to work on real problems.
By Alice Raffaele @AliceRaffaele1
About the Author:
Alice Raffaele is a PhD student in Operations Research from Italy. She is finishing her first year and is interested in OR at 360 degrees. From modelling to polyhedral analysis, but mostly its applications to industrial problems and the interplay between optimisation and data science. She enjoys educational mathematics, i.e. activities and games for children attending primary and secondary schools, to make them discover the beauty of maths and problem solving.
MI-NET 