Adaptive Memory Programming for a Class of Demand Responsive Transit Systems

Abstract

In this paper we discuss Demand Adaptive Systems (DAS) which are intended as a hybrid public transportation system that integrates traditional bus transportation and on demand service, DAS lines regularly serve a given set of compulsory stops according to a predefined schedule and regardless of current demand. Between a compulsory stop and the next, optional stops can be activated on demand. Vehicles have to be rerouted and scheduled in order to satisfy as many requests as possible, complying with passage-time constraints at compulsory stops. This paper provides a general description of DAS, and discusses potential applications and solution methods, emphasizing differences and analogies with classical Demand Responsive Systems. The particular mathematical structure of DAS requires innovative solution methods even when addressing its simplest version, the single vehicle, single line case. An efficient meta-heuristic algorithm based on adaptive memory ideas has been developed for this case. The method integrates sophisticated mathematical programming tools into a tabu search framework, taking advantage of the particular structure of the problem. The methodology is briefly discussed and experimental results are presented for the single line case. We show that the basic case can be efficiently solved, thus providing efficient algorithmic building blocks for more comprehensive approaches tackling the general case.