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A parallel hybrid evolutionary metaheuristic for the period vehicle routing problem

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Book cover Parallel and Distributed Processing (IPPS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1586))

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Abstract

This paper presents a Parallel Hybrid Evolutionary Metaheuristic for the Period Vehicle Routing Problem (PVRP). The PRVP generalizes the classical Vehicle Routing Problem by extending the planning period from a single day to M days. The algorithm proposed is based on concepts used in Parallel Genetic Algorithms and Local Search Heuristics. The algorithm employs the island model in which the migration frequency must not be very high. The results of computational experiments carried out on problems taken from the literature indicate that the proposed approach outperforms existing heuristics in most cases.

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Authors and Affiliations

  1. Departamento de Ciência da Computação, Universidade Federal Fluminense, Travessa Capitão Zeferino 56/808 Niterói, 24220-230, Rio de Janeiro, Brazil

    Dalessandro Soares Vianna, Luiz S. Ochi & Lúcia M. A. Drummond

Authors
  1. Dalessandro Soares Vianna
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  2. Luiz S. Ochi
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  3. Lúcia M. A. Drummond
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Editor information

José Rolim Frank Mueller Albert Y. Zomaya Fikret Ercal Stephan Olariu Binoy Ravindran Jan Gustafsson Hiroaki Takada Ron Olsson Laxmikant V. Kale Pete Beckman Matthew Haines Hossam ElGindy Denis Caromel Serge Chaumette Geoffrey Fox Yi Pan Keqin Li Tao Yang G. Chiola G. Conte L. V. Mancini Domenique Méry Beverly Sanders Devesh Bhatt Viktor Prasanna

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© 1999 Springer-Verlag

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Vianna, D.S., Ochi, L.S., Drummond, L.M.A. (1999). A parallel hybrid evolutionary metaheuristic for the period vehicle routing problem. In: Rolim, J., et al. Parallel and Distributed Processing. IPPS 1999. Lecture Notes in Computer Science, vol 1586. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0097899

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  • DOI: https://doi.org/10.1007/BFb0097899

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65831-3

  • Online ISBN: 978-3-540-48932-0

  • eBook Packages: Springer Book Archive

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