New Heuristic Algorithms for the Crew Scheduling Problem

Abstract

In this paper we describe the implementation of two Tabu search based algorithms for the Crew Scheduling Problem (CSP). The problem is a standard CSP, for an urban transport problem, formulated as the minimal number of duties necessary to cover a predefined timetable under contractual rules which excludes the possibility of resorting to extra-time. The initial solution is obtained with a run-cutting algorithm. Two algorithms are proposed to improve that initial solution. In the first algorithm the run-cutting procedure is applied again to a subset of the problem in a Tabu search framework guided by a strategic oscillation procedure. The second algorithm uses block partition and matching algorithms embedded in a Tabu subgraph ejection chain to explore the neighborhood. Computational results are presented showing the superior performance of the latter algorithm for the case study.