Improving Vehicle Scheduling Support by Efficient Algorithms

Abstract

In this paper, the minimum fleet size problem is investigated: Find the minimum number of vehicles to serve a set of trips of a given timetable for a transportation system. First, we present an algorithm for the basic problem requiring only linear-time after suitably sorting input data. This improves a quadratic-time greedy algorithm developed in [Su95]. Our algorithm was implemented and tested with real-life data indicating a good performance. Generated diagrams on vehicle standing times are shown to be useful for various tasks. Second, Min-Max-results for the minimum fleet size problem are discussed. We argue that Dilworth’s chain decomposition theorem works only if unrestricted deadheading, i.e., adding non-profit ‘empty’ trips, is permitted and thus its application to the case of railway or airline passenger traffic is misleading. To remedy this lack, we consider a particular network flow model for the no deadheading case, formulate a Min-Max-result, and discuss its implications- along with efficient algorithms-for vehicle as well as trip and deadhead trip scheduling.