Improving railway crew scheduling quality: a hybrid approach

Crew management is a major problem for transportation systems such as airlines, railways and public bus transportation. Advances in scheduling methodologies and decision support systems have been substantial in the last years, but they still need improvement, especially from the computational efficiency and practical point of view. This paper presents a hybrid approach based on search strategies, mathematical programming and fuzzy sets to obtain crew timetables without a rostering step. The approach takes past workload and individual needs into account. This improves timetable quality and employee satisfaction. Computational results and experience with actual data and real world situations are reported