Crew scheduling optimiser assisted tuning and fair satisfaction of personal day off preferences at IO2022

By the hand of authors André Leitão and Jorge Roussado, this event will include the following poster presentations:

• "Automated Assisted Tuning of a Crew Scheduling Optimiser" is co-authored by André F. Leitão, Ricardo L. Saldanha, and João P. Martins. This paper is about the use of optimisers in decision support systems and the required exhaustive process of trial and error, sometimes leading to undesirable solutions. SISCOG authors propose a blackbox optimisation approach to provide automated parameter tuning assistance in the context where parameters are the weights of an objective function defined as a weighted sum of multiple conflicting objectives, such as the total number of duties or the overall working time.

• "Crew Rostering with Fair Satisfaction of Personal Day Off Preferences" is co-authored by Ana Wemans, Jorge Roussado, and Ricardo L. Saldanha. In this paper, SISCOG authors motivated by the need of transit agencies improving employee retention levels and motivation by introducing work-life balance concerns in the planning of crew rosters, present an algorithm for optimising crew rosters in a way that distributes fairly days off among employees according to their personal preferences. Overcoming different challenges, they concluded that their model increases the global satisfaction and the fairness in preference satisfaction, and responds consistently to scenarios with different seniority levels.

IO 2022 is an APDIO Congress on Operations Research (OR) taking place at the University of Évora. This year's theme is “OR in Turbulent Times:  Adaptation and Resilience”, and it is the chance for the OR community to gather and share the latest developments in the field. More info here.