Each year, Catharina Hospital Eindhoven organizes a Science Event in which state-of-the-art research done in collaboration with diverse partners is presented. One of these partners is the Information Systems group of the Department of Industrial Engineering & Innovation Sciences, where there is long-term collaboration on healthcare analytics and healthcare process support.
This year, the annual CZE Science Event took place on April 5th, 2018. The best poster prize was won by Saskia van Loon, PhD student within the Data Science flagship of the IMPULS program and the Information Systems group. Saskia researches the possibilities of using ‘big data’ in supporting medical decision making. In her prize-winning poster, Saskia developed a metabolic health index to quantify the health status of bariatric patients with co-morbidities. The work in collaboration with the Department of Biomedical Technology can help monitor the generic health status of patients over the long-term after an operative intervention.
Every year the Dutch Organization for Scientific Research NWO organizes the ICT.OPEN conference for researchers to share their accomplishments and work in ICT research with industry. The event also encourages researchers to pitch their technology and show its potential for industry during the event in Poster and Research Presentations. This year, two PhD candidates of the IS group – Jason Rhuggenaath and Raoul Nuijten – presented their research to the ICT community. And with success: Raoul Nuijten won the Award for Best Poster Presentation in the category Health. The poster exhibited recent research on the eHealth platform GameBus.
We are pleased to invite you to our next Colloquium IS that will take place on Friday,
April 6, 2018, 12:30 – 13:30 (Paviljoen K.16).
Speaker: Murat Firat
Title: Feeding Evolutionary Algorithm with Column Generation output
Nowadays companies in telecommunication, logistics, and airport operations face large scale optimization problems. These problems are usually scheduling and planning problems. Solving these problems to optimality can be exhaustive, even impossible due to the exponential size of their feasible solution sets. At this point, column generation comes to help by providing us good-quality lower bounds for the relaxations of Mixed Integer Linear Programming (MILP) formulations. In my talk, I will firstly mention the basics of the Column Generation, and secondly explain how the output of Column Generation method can be used as input for an Evolutionary Method.