Head of Innovation at SISCOG. More than 30 years of experience in developing scheduling software solutions in the passenger transit domain with focus on optimisation. Deep knowledge on the processes related with scheduling and management of transit operations. Leads a highly skilled team of mathematicians and software engineers that develop and maintain the optimisation models used in SISCOG software products that provide decision support for scheduling and managing the operations of rail and metros. This optimisation support is part of the systems that are running in Dutch Railways, Norwegian Railways, Finnish Railways, Danish Railways, Suburban Trains of Copenhagen, London Underground, Lisbon Metro, and VIA Rail Canada. Author of 18 scientific publications. Winner of the CASPT Best Practice Paper Award (2015) and of the Innovative Application on Artificial Intelligence award (2012).
Sessions
-
June 07: Leveraging AI and data analysis to achieve a greater all-round performance
Tackling staff shortages: using AI and OR to produce crew rosters with better work-life balance
With the end of Covid-19 lockdowns and layoffs many public transport operators are facing shortages of staff, especially of crew personnel. One way to overcome this challenge is to offer crew members the possibility of improving their work-life balance. This can be achieved by allowing them express individual preferences regarding working times, days off, etc., and allowing operators produce rosters that cover all work and satisfy preferences as much, and as fairly as possible. We show how algorithmic support can be used in practice to perform this difficult job. With the use of CREWS, a digital solution developed by SISCOG that provides decision support for planning and managing staff rosters, we show that our approach, tested with real world scenarios, is capable of obtaining more than 100% increase in preference satisfaction and fairness levels while making sure all work is covered.
