A Bus Driver Scheduling Problem: a new mathematical model and a GRASP approximate solution

• Published in: Journal of heuristics Vol. 17; no. 4; pp. 441 - 466
• Main Authors: De Leone, Renato, Festa, Paola, Marchitto, Emilia
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.08.2011; Springer Science + Business Media; Springer Nature B.V
• Subjects: Artificial Intelligence; Bus drivers; Calculus of Variations and Optimal Control; Optimization; Costs; Decomposition; Heuristic; Linear programming; Management Science; Mathematical models; Mathematics; Mathematics and Statistics; Operations Research; Operations Research/Decision Theory; Public transportation; Scheduling; Statistical analysis; Studies; Transportation industry; Transportation services; Working hours; Italy; Crew and Bus Driver Scheduling Problem; GRASP; Transportation; Meta-heuristics
• ISSN: 1381-1231; 1572-9397
• DOI: 10.1007/s10732-010-9141-3

This paper addresses the problem of determining the best scheduling for Bus Drivers, a -hard problem consisting of finding the minimum number of drivers to cover a set of Pieces-Of-Work (POWs) subject to a variety of rules and regulations that must be enforced such as spreadover and working time. This problem is known in literature as Crew Scheduling Problem and, in particular in public transportation, it is designated as Bus Driver Scheduling Problem. We propose a new mathematical formulation of a Bus Driver Scheduling Problem under special constraints imposed by Italian transportation rules. Unfortunately, this model can only be usefully applied to small or medium size problem instances. For large instances, a Greedy Randomized Adaptive Search Procedure (GRASP) is proposed. Results are reported for a set of real-word problems and comparison is made with an exact method. Moreover, we report a comparison of the computational results obtained with our GRASP procedure with the results obtained by Huisman et al. (Transp. Sci. 39(4):491–502, 2005 ).