Hybrid genetic algorithms for scheduling bus and train drivers

We introduce the subject of bus and train driver scheduling, and outline a standard successful approach (TRACS II) using a blend of heuristics and integer linear programming. We then discuss a few limitations of this system In order to overcome these, we and colleagues have investigated a range of metaheuristics and constraint programming approaches, and some of these are outlined. Finally we present a hybrid genetic algorithm which is successfully used to overcome the above limitations. In this approach, all probable potential shifts are generated according to well developed heuristics already used in TRACS II. Selection of such shifts to form a schedule is modeled as a set covering problem, and the relaxation of this problem ignoring integer conditions is solved to optimality, A GA then develops a solution schedule based on some of the characteristics of the relaxed solution. It is suggested that this approach might be suitable for other set covering problems.