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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2011: Evolutionary Multi-Criterion Optimization pp 535–549Cite as

GRACE: A Generational Randomized ACO for the Multi-objective Shortest Path Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6576))

Abstract

The Multi-objective Shortest Path Problem (MSP) is a widely studied NP-Hard problem. A few exact algorithms were already proposed to solve this problem, however none is able to solve large instances with three or more objectives. Recently, some metaheuristics have been proposed for the MSP, but little can be said about their efficiency regarding each other, since no comparisons among them are presented in the literature. In this paper an Ant Colony Optimization (ACO) algorithm, called GRACE, is proposed for the MSP. The proposed approach is compared to the well-known evolutionary algorithm NSGA-II. Furthermore, GRACE is compared to another ACO algorithm proposed previously for the MSP. Results of a computational experiment with eighteen instances, with three objectives each, show that the proposed approach is able to produce high quality results for the tested instances.

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Author information

Authors and Affiliations

  1. Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil

    Leonardo C. T. Bezerra, Elizabeth F. G. Goldbarg & Marco C. Goldbarg

  2. Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil

    Luciana S. Buriol

Authors
  1. Leonardo C. T. Bezerra
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  2. Elizabeth F. G. Goldbarg
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  3. Luciana S. Buriol
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  4. Marco C. Goldbarg
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil

    Ricardo H. C. Takahashi

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Av. Amazonas 5253, 30421-169, Belo Horizonte, MG, Brazil

    Elizabeth F. Wanner

  4. Faculty of Economics, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

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© 2011 Springer-Verlag Berlin Heidelberg

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Bezerra, L.C.T., Goldbarg, E.F.G., Buriol, L.S., Goldbarg, M.C. (2011). GRACE: A Generational Randomized ACO for the Multi-objective Shortest Path Problem. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_37

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  • DOI: https://doi.org/10.1007/978-3-642-19893-9_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19892-2

  • Online ISBN: 978-3-642-19893-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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