A Hybrid genetic algorithm for the vehicle and crew scheduling in mass transit systems

Abstract

The integrated vehicle and crew scheduling problem is a difficult and widely studied Combinatorial Optimization problem. Several studies have shown that exact approaches for this problem are not useful in practical situations due to the high computational costs involved. This paper describes a hybrid genetic algorithm for vehicle and crew scheduling, which is modeled as a maximal covering problem with multiples resources. In addition, an innovative mathematical formulation is presented. Computational results with real vehicle and crew scheduling problem instances are presented and discussed. These results indicate that the proposed approach has a considerable potential for achieving significant gains in terms of operation costs and planning times.