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A Genetic Algorithm with Grouping Selection and Searching Operators for the Orienteering Problem

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Intelligent Information and Database Systems (ACIIDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9012))

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Abstract

In the Orienteering Problem (OP), a set of linked vertices, each with a score, is given. The objective is to find a route, limited in length, over a subset of vertices that maximises the collective score of the visited vertices. In this paper, we present a new, efficient genetic algorithm (nGA) that solves the OP. We use a special grouping during selection, which results in better-adapted routes in the population. Furthermore, we apply a searching crossover to each generation, which uses the common vertices between distinct routes in the population; we also apply a searching mutation. Computer experiments on the nGA are conducted on popular data sets. In some cases, the nGA yields better results than well-known heuristics.

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Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Białystok, Poland

    Pawel Zabielski, Joanna Karbowska-Chilinska, Jolanta Koszelew & Krzysztof Ostrowski

Authors
  1. Pawel Zabielski
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  2. Joanna Karbowska-Chilinska
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  3. Jolanta Koszelew
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  4. Krzysztof Ostrowski
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Corresponding authors

Correspondence to Pawel Zabielski or Joanna Karbowska-Chilinska .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University, Ho Chi Minh city, Vietnam

    Ngoc Thanh Nguyen

  2. Wroclaw University of Technology, Wroclaw, Poland

    Bogdan Trawiński

  3. Bina Nusantara University, Jakarta, Indonesia

    Raymond Kosala

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Zabielski, P., Karbowska-Chilinska, J., Koszelew, J., Ostrowski, K. (2015). A Genetic Algorithm with Grouping Selection and Searching Operators for the Orienteering Problem. In: Nguyen, N., Trawiński, B., Kosala, R. (eds) Intelligent Information and Database Systems. ACIIDS 2015. Lecture Notes in Computer Science(), vol 9012. Springer, Cham. https://doi.org/10.1007/978-3-319-15705-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-15705-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15704-7

  • Online ISBN: 978-3-319-15705-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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