A Study on Genetic Algorithms for the DARP Problem

Authors:
Claudio Cubillos;Nibaldo Rodriguez;Broderick Crawford
Affiliations:
Pontificia Universidad Católica de Valparaíso, Escuela de Ingeniería Informática, Av. Brasil 2241, Valparaíso, Chile;Pontificia Universidad Católica de Valparaíso, Escuela de Ingeniería Informática, Av. Brasil 2241, Valparaíso, Chile;Pontificia Universidad Católica de Valparaíso, Escuela de Ingeniería Informática, Av. Brasil 2241, Valparaíso, Chile
Venue:
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Year:
2007

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Abstract

This work presents the results on applying a genetic approach for solving the Dial-A-Ride Problem (DARP). The problem consists of assigning and scheduling a set of user transport requests to a fleet of available vehicles in the most efficient way according to a given objective function. The literature offers different heuristics for solving DARP, a well known NP-hard problem, which range from traditional insertion and clustering algorithms to soft computing techniques. On the other hand, the approach through Genetic Algorithms (GA) has been experienced in problems of combinatorial optimization. We present our experience and results of a study to develop and test different GAs in the aim of finding an appropriate encoding and configuration, specifically for the DARP problem with time windows.