Building Heuristics and Ensembles for the Travel Salesman Problem
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{10.1007/978-3-031-06527-9_13,
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author = "Francisco J. Gil-Gala and Marko Durasevic and
Maria R. Sierra and Ramiro Varela",
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title = "Building Heuristics and Ensembles for the Travel
Salesman Problem",
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booktitle = "Proceedings of the 9th International Work-Conference
on the Interplay Between Natural and Artificial
Computation, IWINAC 2022, Part II",
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year = "2022",
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editor = "Jose Manuel Ferrandez Vicente and
Jose Ramon Alvarez-Sanchez and Felix de la Paz Lopez and
Hojjat Adeli",
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volume = "13259",
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series = "LNCS",
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pages = "130--139",
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address = "Puerto de la Cruz, Tenerife, Spain",
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month = may # " 31-" # jun # " 3",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-031-06527-9",
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DOI = "doi:10.1007/978-3-031-06527-9_13",
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abstract = "The Travel Salesman Problem (TSP) is one of the most
studied optimization problems due to its high
difficulty and its practical interest. In some
real-life applications of this problem the solution
methods must be very efficient to deal with dynamic
environments or large problem instances. For this
reasons, low time consuming heuristics as priority
rules are often used. Even though such a single
heuristic may be good to solve many instances, it may
not be robust enough to take the best decisions in all
situations so, we hypothesise that an ensemble of
heuristics could be much better than the best of those
heuristic. We view an ensemble as a set of heuristics
that collaboratively build a single solution by
combining the decisions of each individual heuristic.
In this paper, we study the application of single
heuristics and ensembles to the TSP. The individual
heuristics are evolved by Genetic Programming (GP) and
then Genetic Algorithms (GA) are used to build
ensembles from a pool of single heuristics. We
conducted an experimental study on a set of instances
taken from the TSPLIB. The results of this study
provided interesting insights about the behaviour of
rules and ensembles.",
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notes = "Published as Bio-inspired Systems and Applications:
from Robotics to Ambient Intelligence",
- }
Genetic Programming entries for
Francisco Javier Gil Gala
Marko Durasevic
Maria Rita Sierra Sanchez
Ramiro Varela Arias
Citations