Citation
A Hybrid of Differential Evolution and Simulated Annealing Algorithms for the Capacitated Arc Routing Problems. In proceedings of the 6th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2013), 27 - 30 Aug 2013, Ghent, Belgium, pages 549-554, 2013.
Paper
Abstract
The capacitated arc routing problem (CARP) is a variation of the classic vehicle routing problem in which the objective is to minimize the cost of serving a subset of required arcs without violating vehicle capacity. CARP is an NP-hard combinatorial optimization problem and has many real world applications such as mail delivery, street sweeping and garbage collection. Differential evolution is a population based algorithm that has been shown to be competitive when compared to other methods when tested on continuous optimization problems. In this work, we propose differential evolution as a suitable methodology for combinatorial problems. We use a random key encoding scheme in order to apply differential evolution to combinatorial optimization problems. The exploitation of differential evolution is enhanced by hybridizing it with simulated annealing. Experimental results on CARP benchmark instances demonstrate that the proposed hybrid algorithm obtains very good results, producing new best results for some instances when compared to other state of the art methods.
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Bibtex
@INPROCEEDINGS{2013-549-554-P, author = {N.R. Sabar and M. Ayob and G. Kendall},
title = {A Hybrid of Differential Evolution and Simulated Annealing Algorithms for the Capacitated Arc Routing Problems},
booktitle = {In proceedings of the 6th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2013), 27 - 30 Aug 2013, Ghent, Belgium},
year = {2013},
editor = {G. Kendall and B. McCollum and G. {Venden Berghe}},
pages = {549--554},
note = {Paper},
abstract = {The capacitated arc routing problem (CARP) is a variation of the classic vehicle routing problem in which the objective is to minimize the cost of serving a subset of required arcs without violating vehicle capacity. CARP is an NP-hard combinatorial optimization problem and has many real world applications such as mail delivery, street sweeping and garbage collection. Differential evolution is a population based algorithm that has been shown to be competitive when compared to other methods when tested on continuous optimization problems. In this work, we propose differential evolution as a suitable methodology for combinatorial problems. We use a random key encoding scheme in order to apply differential evolution to combinatorial optimization problems. The exploitation of differential evolution is enhanced by hybridizing it with simulated annealing. Experimental results on CARP benchmark instances demonstrate that the proposed hybrid algorithm obtains very good results, producing new best results for some instances when compared to other state of the art methods. },
owner = {Graham},
timestamp = {2017.01.16},
webpdf = {2013-549-554-P.pdf} }