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A Sampling-Based Metaheuristic for the Orienteering Problem with Stochastic Travel Times

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Theory and Practice of Natural Computing (TPNC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10071))

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Abstract

In this paper we propose a new metaheuristic approach based on sampling for the Orienteering Problem with Stochastic Travel Times (OPSTS). As in many Stochastic Combinatorial Optimization Problems, the computational bottleneck of OPSTS is in the objective function evaluation. For this reason, this study is mainly devoted to the development and integration of on-purpose, sampling-based fast objective function evaluations into metaheuristic methods. In details, we show how a Variable Neighbourhood Search Metaheuristic can be enhanced by adopting such evaluators. Experimental results show that the new sampling-based method is faster than conventional methods for the given problem, and the improvement is particularly relevant for large-scale instances.

V. Papapanagiotou—Supported by the Swiss National Science Foundation through project 200020-156259/1: “Hybrid Sampling-based Metaheuristics for Stochastic Optimization Problems with Deadlines”.

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Authors and Affiliations

  1. IDSIA, Dalle Molle Institute for Artificial Intelligence, USI-SUPSI, Manno-Lugano, Switzerland

    Vassilis Papapanagiotou, Roberto Montemanni & Luca Maria Gambardella

Authors
  1. Vassilis Papapanagiotou
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  2. Roberto Montemanni
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  3. Luca Maria Gambardella
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Corresponding author

Correspondence to Roberto Montemanni .

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Editors and Affiliations

  1. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  2. Tohoku University, Sendai, Japan

    Takaaki Mizuki

  3. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

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Papapanagiotou, V., Montemanni, R., Gambardella, L.M. (2016). A Sampling-Based Metaheuristic for the Orienteering Problem with Stochastic Travel Times. In: Martín-Vide, C., Mizuki, T., Vega-Rodríguez, M. (eds) Theory and Practice of Natural Computing. TPNC 2016. Lecture Notes in Computer Science(), vol 10071. Springer, Cham. https://doi.org/10.1007/978-3-319-49001-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-49001-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49000-7

  • Online ISBN: 978-3-319-49001-4

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