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Hyper-heuristics, grammatical evolution and the capacitated vehicle routing problem

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GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

Pages 71 - 72

https://doi.org/10.1145/2598394.2598407

Published: 12 July 2014 Publication History

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Abstract

A common problem when applying heuristics is that they often perform well on some problem instances, but poorly on others. We develop a hyper-heuristic approach, using Grammatical Evolution (GE), to generate heuristics for the Vehicle Routing Problem (VRP). Through a series of experiments we develop an approach that leads to solutions of acceptable quality to Vehicle Routing Problem instances with only limited prior knowledge of the problem to be solved.

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Cited By

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Costa JMei YZhang M(2020)Adaptive Search Space through Evolutionary Hyper-Heuristics for the Large-Scale Vehicle Routing Problem2020 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI47803.2020.9308239(2415-2422)Online publication date: 1-Dec-2020
https://doi.org/10.1109/SSCI47803.2020.9308239
Costa JMei YZhang M(2020)Cluster-based Hyper-Heuristic for Large-Scale Vehicle Routing Problem2020 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC48606.2020.9185831(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/CEC48606.2020.9185831
Yu VMaglasang RTsao Y(2020)A reduced variable neighborhood search-based hyperheuristic for the shelf space allocation problemComputers & Industrial Engineering10.1016/j.cie.2020.106420143(106420)Online publication date: May-2020
https://doi.org/10.1016/j.cie.2020.106420
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Index Terms

Hyper-heuristics, grammatical evolution and the capacitated vehicle routing problem
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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A Combined Generative and Selective Hyper-heuristic for the Vehicle Routing Problem
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Published In

GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

July 2014

1524 pages

ISBN:9781450328814

DOI:10.1145/2598394

Editor-in-chief:
Christian Igel
Ruhr University of Bochum, University of Copenhagen
,
General Chair:
Dirk V. Arnold
Dalhousie University

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 12 July 2014

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SIGEVO

GECCO '14: Genetic and Evolutionary Computation Conference

July 12 - 16, 2014

BC, Vancouver, Canada

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GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Costa JMei YZhang M(2020)Adaptive Search Space through Evolutionary Hyper-Heuristics for the Large-Scale Vehicle Routing Problem2020 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI47803.2020.9308239(2415-2422)Online publication date: 1-Dec-2020
https://doi.org/10.1109/SSCI47803.2020.9308239
Costa JMei YZhang M(2020)Cluster-based Hyper-Heuristic for Large-Scale Vehicle Routing Problem2020 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC48606.2020.9185831(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/CEC48606.2020.9185831
Yu VMaglasang RTsao Y(2020)A reduced variable neighborhood search-based hyperheuristic for the shelf space allocation problemComputers & Industrial Engineering10.1016/j.cie.2020.106420143(106420)Online publication date: May-2020
https://doi.org/10.1016/j.cie.2020.106420
Tarhini ADanach KHarfouche A(2020)Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customersAnnals of Operations Research10.1007/s10479-020-03625-5Online publication date: 7-May-2020
https://doi.org/10.1007/s10479-020-03625-5
Epitropakis MBurke E(2018)Hyper-heuristicsHandbook of Heuristics10.1007/978-3-319-07153-4_32-1(1-57)Online publication date: 10-Feb-2018
https://doi.org/10.1007/978-3-319-07153-4_32-1
Epitropakis MBurke E(2018)Hyper-heuristicsHandbook of Heuristics10.1007/978-3-319-07124-4_32(489-545)Online publication date: 14-Aug-2018
https://doi.org/10.1007/978-3-319-07124-4_32
Espinoza-Nevárez DOrtiz-Bayliss JTerashima-Marín HGatica GNeumann FSutton A(2016)Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time WindowsProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2909051(139-140)Online publication date: 20-Jul-2016
https://dl.acm.org/doi/10.1145/2908961.2909051
Mariani TGuizzo GVergilio SPozo ANeumann FSutton A(2016)Grammatical Evolution for the Multi-Objective Integration and Test Order ProblemProceedings of the Genetic and Evolutionary Computation Conference 201610.1145/2908812.2908816(1069-1076)Online publication date: 20-Jul-2016
https://dl.acm.org/doi/10.1145/2908812.2908816

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A Combined Generative and Selective Hyper-heuristic for the Vehicle Routing Problem

Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows

Applying hybrid meta-heuristics for capacitated vehicle routing problem

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A Combined Generative and Selective Hyper-heuristic for the Vehicle Routing Problem

Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows

Applying hybrid meta-heuristics for capacitated vehicle routing problem

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