Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28894
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A New Generalized Partition Crossover for the Traveling Salesman Problem: Tunneling Between Local Optima
Author(s): Tinós, Renato
Whitley, Darrell
Ochoa, Gabriela
Contact Email: gabriela.ochoa@stir.ac.uk
Keywords: Traveling salesman problem
recombination operator
evolutionary combinatorial op- timization
Issue Date: 1-Jun-2020
Date Deposited: 4-Mar-2019
Citation: Tinós R, Whitley D & Ochoa G (2020) A New Generalized Partition Crossover for the Traveling Salesman Problem: Tunneling Between Local Optima. Evolutionary Computation, 28 (2), pp. 255-288. https://doi.org/10.1162/evco_a_00254
Abstract: Generalized Partition Crossover (GPX) is a deterministic recombination operator developed for the Traveling Salesman Problem. Partition crossover operators return the best of 2 k reachable offspring, where k is the number of recombining components. This paper introduces a new GPX2 operator, which finds more recombining components than GPX or Iterative Partial Transcription (IPT). We also show that GPX2 has O(n) runtime complexity, while also introducing new enhancements to reduce the execution time of GPX2. Finally, we experimentally demonstrate the efficiency of GPX2 when it is used to improve solutions found by multi-trial Lin-Kernighan-Helsgaum (LKH) algorithm. Significant improvements in performance are documented on large (n > 5000) and very large (n = 100, 000) instances of the Traveling Salesman Problem.
DOI Link: 10.1162/evco_a_00254
Rights: This is is the author's final version of an article accepted for publication in Evolutionary Computation published by MIT Press. https://doi.org/10.1162/evco_a_00254
Licence URL(s): https://storre.stir.ac.uk/STORREEndUserLicence.pdf

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