research-article

Computing single source shortest paths using single-objective fitness

Authors:

Surender Baswana,

Somenath Biswas,

Benjamin Doerr,

Tobias Friedrich,

Piyush P. Kurur,

Frank NeumannAuthors Info & Claims

FOGA '09: Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms

Pages 59 - 66

https://doi.org/10.1145/1527125.1527134

Published: 09 January 2009 Publication History

Abstract

Runtime analysis of evolutionary algorithms has become an important part in the theoretical analysis of randomized search heuristics. The first combinatorial problem where rigorous runtime results have been achieved is the well-known single source shortest path (SSSP) problem. Scharnow, Tinnefeld and Wegener [PPSN 2002, J. Math. Model. Alg. 2004] proposed a multi-objective approach which solves the problem in expected polynomial time. They also suggest a related single-objective fitness function. However, it was left open whether this does solve the problem efficiently, and, in a broader context, whether multi-objective fitness functions for problems like the SSSP yield more efficient evolutionary algorithms. In this paper, we show that the single objective approach yields an efficient (1+1) EA with runtime bounds very close to those of the multi-objective approach.

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Cited By

Sudholt D(2020)Analysing the Robustness of Evolutionary Algorithms to Noise: Refined Runtime Bounds and an Example Where Noise is BeneficialAlgorithmica10.1007/s00453-020-00671-0Online publication date: 25-Jan-2020
https://doi.org/10.1007/s00453-020-00671-0
Mühlenthaler MRaß A(2019)Runtime analysis of discrete particle swarm optimization algorithms: A surveyit - Information Technology10.1515/itit-2019-000961:4(177-185)Online publication date: 24-Oct-2019
https://doi.org/10.1515/itit-2019-0009
Doerr BAuger AStützle T(2019)Theory for non-theoreticiansProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3319619.3323373(523-549)Online publication date: 13-Jul-2019
https://dl.acm.org/doi/10.1145/3319619.3323373
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Index Terms

Computing single source shortest paths using single-objective fitness
1. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Sorting and searching

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cover image ACM Conferences

FOGA '09: Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms

January 2009

204 pages

ISBN:9781605584140

DOI:10.1145/1527125

General Chairs:
Ivan Garibay
University of Central Florida
,
Thomas Jansen
Technische Universität Dortmund
,
R. Paul Wiegand
University of Central Florida
,
Annie S. Wu
University of Central Florida

Copyright © 2009 ACM.

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Publication History

Published: 09 January 2009

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shortest path

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FOGA '09

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FOGA '09: Foundations of Genetic Algorithms X

January 9 - 11, 2009

Florida, Orlando, USA

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FOGA '09 Paper Acceptance Rate 18 of 30 submissions, 60%;

Overall Acceptance Rate 72 of 131 submissions, 55%

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Cited By

Sudholt D(2020)Analysing the Robustness of Evolutionary Algorithms to Noise: Refined Runtime Bounds and an Example Where Noise is BeneficialAlgorithmica10.1007/s00453-020-00671-0Online publication date: 25-Jan-2020
https://doi.org/10.1007/s00453-020-00671-0
Mühlenthaler MRaß A(2019)Runtime analysis of discrete particle swarm optimization algorithms: A surveyit - Information Technology10.1515/itit-2019-000961:4(177-185)Online publication date: 24-Oct-2019
https://doi.org/10.1515/itit-2019-0009
Doerr BAuger AStützle T(2019)Theory for non-theoreticiansProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3319619.3323373(523-549)Online publication date: 13-Jul-2019
https://dl.acm.org/doi/10.1145/3319619.3323373
Ezzeldin MEl-Dakhakhni W(2019)Robustness of Ontario power network under systemic risksSustainable and Resilient Infrastructure10.1080/23789689.2019.1666340(1-20)Online publication date: 2-Oct-2019
https://doi.org/10.1080/23789689.2019.1666340
Doerr BDoerr CYang J(2019)Optimal Parameter Choices via Precise Black-Box AnalysisTheoretical Computer Science10.1016/j.tcs.2019.06.014Online publication date: Jul-2019
https://doi.org/10.1016/j.tcs.2019.06.014
Raß ASchreiner JWanka R(2019)Runtime Analysis of Discrete Particle Swarm Optimization Applied to Shortest Paths ComputationEvolutionary Computation in Combinatorial Optimization10.1007/978-3-030-16711-0_8(115-130)Online publication date: 24-Apr-2019
https://dl.acm.org/doi/10.1007/978-3-030-16711-0_8
Doerr BTakadama K(2018)Theory for non-theoreticiansProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3205651.3207889(389-414)Online publication date: 6-Jul-2018
https://dl.acm.org/doi/10.1145/3205651.3207889
Sudholt DTakadama K(2018)On the robustness of evolutionary algorithms to noiseProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205595(1523-1530)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3205455.3205595
Doerr B(2017)Theory for non-theoreticiansProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3067713(389-412)Online publication date: 15-Jul-2017
https://dl.acm.org/doi/10.1145/3067695.3067713
Dib OMoalic LManier MCaminada A(2017)An advanced GAVNS combination for multicriteria route planning in public transit networksExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.12.00972:C(67-82)Online publication date: 15-Apr-2017
https://dl.acm.org/doi/10.1016/j.eswa.2016.12.009
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