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A Memetic-GRASP Algorithm for the Solution of the Orienteering Problem

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 360)

Abstract

The last decade a large number of applications in logistics, tourism and other fields have been studied and modeled as Orienteering Problems (OPs). In the orienteering problem, a standard amount of nodes are given, each with a specific score. The goal is to determine a path, limited in length, from the start point to the end point through a subset of locations in order to maximize the total path score. In this paper, we present a new hybrid evolutionary algorithm for the solution of the Orienteering Problem. The algorithm combines a Greedy Randomized Adaptive Search Procedure (GRASP), an Evolutionary Algorithm and two local search procedures. The algorithm was tested in a number of benchmark instances from the literature and in most of them the best known solutions were found.

Keywords

  • Orienteering Problem
  • Memetic Algorithm
  • Greedy Randomized Adaptive Search Procedure
  • Local Search

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Correspondence to Yannis Marinakis .

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Marinakis, Y., Politis, M., Marinaki, M., Matsatsinis, N. (2015). A Memetic-GRASP Algorithm for the Solution of the Orienteering Problem. In: Le Thi, H., Pham Dinh, T., Nguyen, N. (eds) Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-18167-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-18167-7_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18166-0

  • Online ISBN: 978-3-319-18167-7

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