research-article

Parameter-less late acceptance hill-climbing

Authors:

Mosab Bazargani,

Fernando G. LoboAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference

Pages 219 - 226

https://doi.org/10.1145/3071178.3071225

Published: 01 July 2017 Publication History

Abstract

The Late Acceptance Hill-Climbing (LAHC) algorithm has been recently introduced by Burke and Bykov. It is a simple, general purpose, one-point search metaheuristic that has similarities with Simulated Annealing (SA) in the sense that worsening moves on a current solution can be accepted. One of its advantages relative to Simulated Annealing is that no cooling schedule is required and its sole parameter, the so-called history length, has a more meaningful interpretation from the application point of view and is therefore easier to specify by a user. In this paper we show that even this single parameter can be eliminated, making LAHC simpler to apply in practice. The validity of the method is shown with computational experiments on a number of instances of the Travelling Salesman Problem.

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Cited By

Sae-Dan WKessaci MVeerapen NJourdan L(2022)Automatic Algorithm Multi-Configuration Applied to an Optimization AlgorithmHybrid Intelligent Systems10.1007/978-3-030-96305-7_15(160-170)Online publication date: 4-Mar-2022
https://doi.org/10.1007/978-3-030-96305-7_15
Beham AWagner SAffenzeller MTakadama K(2018)Algorithm selection on generalized quadratic assignment problem landscapesProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205585(253-260)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3205455.3205585
Bazargani MDrake JBurke E(2018)Late Acceptance Hill Climbing for Constrained Covering ArraysApplications of Evolutionary Computation10.1007/978-3-319-77538-8_52(778-793)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_52
Show More Cited By

Index Terms

Parameter-less late acceptance hill-climbing
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Randomized search
  2. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Optimization algorithms

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cover image ACM Conferences

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference

July 2017

1427 pages

ISBN:9781450349208

DOI:10.1145/3071178

General Chair:
Peter A. N. Bosman
Centrum Wiskunde & Informatica (CWI)

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

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Published: 01 July 2017

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GECCO '17

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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GECCO '17 Paper Acceptance Rate 178 of 462 submissions, 39%;

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

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Cited By

Sae-Dan WKessaci MVeerapen NJourdan L(2022)Automatic Algorithm Multi-Configuration Applied to an Optimization AlgorithmHybrid Intelligent Systems10.1007/978-3-030-96305-7_15(160-170)Online publication date: 4-Mar-2022
https://doi.org/10.1007/978-3-030-96305-7_15
Beham AWagner SAffenzeller MTakadama K(2018)Algorithm selection on generalized quadratic assignment problem landscapesProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205585(253-260)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3205455.3205585
Bazargani MDrake JBurke E(2018)Late Acceptance Hill Climbing for Constrained Covering ArraysApplications of Evolutionary Computation10.1007/978-3-319-77538-8_52(778-793)Online publication date: 8-Mar-2018
https://doi.org/10.1007/978-3-319-77538-8_52
Namazi MSanderson CNewton MPolash MSattar A(2018)Diversified Late Acceptance SearchAI 2018: Advances in Artificial Intelligence10.1007/978-3-030-03991-2_29(299-311)Online publication date: 10-Nov-2018
https://doi.org/10.1007/978-3-030-03991-2_29

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