Scheduling of Drivers for Mass Transit Systems Using Interactive Optimisation

This paper presented a mode for formulating and solving the mass transit crew/vehicle scheduling problem. This model offers a large degree of flexibility because of its use of man/machine interaction. In particular, it allows the human scheduler to involve constraints and to guide the algorithm dynamically as it searches for a low cost solution. The paper presented computational results from a non-interactive version of the algorithm on a data base from the city of Baltimore. These results show that the model provides a viable approach to the problem.