Meta-Heuristics for a Class of Demand-Responsive Transit Systems

  • Authors:

  • Teodor Gabriel Crainic;Federico Malucelli;Maddalena Nonato;François Guertin

  • Affiliations:

  • Département de Management et Technologie, Université du Québec á Montréal, and Centre de Recherche sur les Transports, Université de Montréal, C.P. 6128, Succ. C ...;Dipartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy;Dipartimento di Ingegneria Elettronica e dell'Informazione, Università di Perugia, via G. Duranti, Santa Lucia Canetola 06125 PG, Italy;Centre de Recherche sur les Transports, Université de Montréal, C.P. 6128, Succ. Centre-ville, Montréal, QC, Canada H3C 3J7

  • Venue:
  • INFORMS Journal on Computing
  • Year:
  • 2005

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Abstract

The demand-adaptive systems studied in this paper attempt to offer demand-responsive services within the framework of traditional scheduled bus transportation: Users call to request service between two given points and, in so doing, induce detours in the vehicle routes; at the same time, though, a given set of compulsory stops is always served according to a predefined schedule, regardless of the current set of active requests. The model developed to select requests and determine the routing of the vehicle yields a difficult formulation but with a special structure that may be used to develop efficient algorithms. In this paper, we develop, test, and compare several solution strategies for the single line-single vehicle problem that belong to two general meta-heuristic classes, memory-enhanced greedy randomized multistart constructive procedures, and tabu search methods. Hybrid meta-heuristics combining the two methods are also analyzed.