Application of Genetic Algorithms for the DARPTW Problem

Authors

  • Claudio Cubillos Pontificia Universidad Católica de Valparaí­so Escuela de Ingenierí­a Informí¡tica Av. Brasil 2241, Valparaí­so, Chile
  • Enrique Urra Pontificia Universidad Católica de Valparaí­so Escuela de Ingenierí­a Informí¡tica Av. Brasil 2241, Valparaí­so, Chile
  • Nibaldo Rodrí­guez Pontificia Universidad Católica de Valparaí­so Escuela de Ingenierí­a Informí¡tica Av. Brasil 2241, Valparaí­so, Chile

Keywords:

Dial-a-ride, Passenger Transportation, DARPTW, Heuristic, Scheduling

Abstract

On the Dial-a-Ride with time windows (DARPTW) customer transportation problem, there is a set of requests from customers to be transported from an origin place to a delivery place through a locations network, under several constraints like the time windows. The problem complexity (NP-Hard) forces the use of heuristics on its resolution. In this context, the application of Genetic Algorithms (GA) on DARPTW was not largely considered, with the exception of a few researches. In this work, under a restrictive scenario, a GA model for the problem was developed based on the adaptation of a generic GA model from literature. Our solution applies data pre-processing techniques to reduce the search space to points that are feasible regarding time windows constraints. Tests show competitive results on Cordeau & Laporte benchmark datasets while improving processing times.

References

K. Bergvinsdottir, The Genetic Algorithm for solving the Dial-a-Ride Problem, Master's thesis, Informatics and Mathematical Modelling, Technical University of Denmark, DTU, 2004.

R. M. Jorgensen, J. Larsen, K. B. Bergvinsdottir, Solving the Dial-a-Ride problem using genetic algorithms, J. Oper. Res. Soc., Vol.58, pp. 1321-1331, 2006. http://dx.doi.org/10.1057/palgrave.jors.2602287

J. Cordeau, A Branch-and-Cut Algorithm for the Dial-a-Ride Problem, Operations Research, Vol. 54, pp. 573-586, 2006. http://dx.doi.org/10.1287/opre.1060.0283

J. Cordeau, G. Laporte, A tabu search heuristic for the static multi-vehicle dial-a-ride problem, Transportation Research Part B, Vol. 37, Issue 6, pp. 579-594, 2003. http://dx.doi.org/10.1016/S0191-2615(02)00045-0

J. Cordeau, G. Laporte, Benchmark datasets accessed on march-2007, available online at: http://neumann.hec.ca/chairedistributique/data/darp/. 2007.

C. Cubillos, MADARP: Multi-Agent Framework for Transportation Systems, Thesis for the academic degree of Dottore di Ricerca in Ingegneria Informatica e dei Sistemi (ciclo XVII), Politecnico di Torino, 2005.

C. Cubillos, N. Rodriguez, B. Crawford, A Study on Genetic Algorithms for the DARP Problem, Springer Berlin-Heidelberg LNCS, vol. 4527, pp. 498-507, 2007. http://dx.doi.org/10.1007/978-3-540-73053-8_50

G. Harik, D.E. Goldberg, Learning linkage, Foundations of Genetic Algorithms, vol. 4, pp. 247-262, 1996.

J.H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to biology, control and artificial intelligence, MIT Press, ISBN 0-262-58111-6, 1998.

M.W.P. Savelsbergh, The General Pickup and Delivery Problem, Transportation Science, Vol. 29, pp. 17-29, 1995. http://dx.doi.org/10.1287/trsc.29.1.17

S. Thangiah, Vehicle Routing with Time Windows using Genetic Algorithms, Application Handbook of Genetic Algorithms: New Frontiers, Vol. II. Lance Chambers (Ed.). CRC Press, 1995.

Published

2009-06-01

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