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Mathematical Problems in Engineering
Volume 2015, Article ID 707056, 12 pages
http://dx.doi.org/10.1155/2015/707056
Research Article

A Hyperheuristic for the Dial-a-Ride Problem with Time Windows

1Escuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2950, 2340025 Valparaíso, Chile
2Escuela de Ingeniería Comercial, Universidad de Valparaíso, Pasaje La Paz 1301, 2531075 Viña del Mar, Chile

Received 25 September 2014; Accepted 15 December 2014

Academic Editor: Haipeng Peng

Copyright © 2015 Enrique Urra et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The dial-a-ride problem with time windows (DARPTW) is a combinatorial optimization problem related to transportation, in which a set of customers must be picked up from an origin location and they have to be delivered to a destination location. A transportation schedule must be constructed for a set of available vehicles, and several constraints have to be considered, particularly time windows, which define an upper and lower time bound for each customer request in which a vehicle must arrive to perform the service. Because of the complexity of DARPTW, a number of algorithms have been proposed for solving the problem, mainly based on metaheuristics such as Genetic Algorithms and Simulated Annealing. In this work, a different approach for solving DARPTW is proposed, designed, and evaluated: hyperheuristics, which are alternative heuristic methods that operate at a higher abstraction level than metaheuristics, because rather than searching in the problem space directly, they search in a space of low-level heuristics to find the best strategy through which good solutions can be found. Although the proposed hyperheuristic uses simple and easy-to-implement operators, the experimental results demonstrate efficient and competitive performance on DARPTW when compared to other metaheuristics from the literature.