research-article

Improved incremental non-dominated sorting for steady-state evolutionary multiobjective optimization

Authors:

Maxim BuzdalovAuthors Info & Claims

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

Pages 649 - 656

https://doi.org/10.1145/3071178.3071307

Published: 01 July 2017 Publication History

Abstract

We present an algorithm for incremental non-dominated sorting, a procedure to use with steady-state multiobjective algorithms, with the complexity of O(N(log N)^M−2) for a single insertion, where N is the number of points and M is the number of objectives. This result generalizes the previously known O(N) algorithm designed for two objectives.

Our experimental performance study showed that our algorithm demonstrates a superior performance compared to the competitors, including various modifications of the divide-and-conquer non-dominated sorting algorithm (which significantly improve the performance on their own), and the state-of-the-art Efficient Non-domination Level Update algorithm. Only for M = 2 the specialized algorithm for two dimensions outperforms the new algorithm.

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Cited By

Mateo PLahoz DAlberto I(2022)Incremental Non-Dominated Sorting algorithms based on Irreducible Domination GraphsApplied Soft Computing10.1016/j.asoc.2022.109466128:COnline publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.asoc.2022.109466
Zhu HJin Y(2021)Toward Real-Time Federated Evolutionary Neural Architecture SearchAutomated Design of Machine Learning and Search Algorithms10.1007/978-3-030-72069-8_8(133-147)Online publication date: 29-Jul-2021
https://doi.org/10.1007/978-3-030-72069-8_8
Mishra SCoello C(2020)A parallel naive approach for non-dominated sorting: a theoretical study considering PRAM CREW modelSoft Computing10.1007/s00500-020-05450-1Online publication date: 26-Nov-2020
https://doi.org/10.1007/s00500-020-05450-1
Show More Cited By

Index Terms

Improved incremental non-dominated sorting for steady-state evolutionary multiobjective optimization
1. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Sorting and searching
    2. Online 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 the author(s) 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

New York, NY, United States

Publication History

Published: 01 July 2017

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Ministry of Education and Science of the Russian Federation

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GECCO '17

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SIGEVO

GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

Acceptance Rates

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

Mateo PLahoz DAlberto I(2022)Incremental Non-Dominated Sorting algorithms based on Irreducible Domination GraphsApplied Soft Computing10.1016/j.asoc.2022.109466128:COnline publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1016/j.asoc.2022.109466
Zhu HJin Y(2021)Toward Real-Time Federated Evolutionary Neural Architecture SearchAutomated Design of Machine Learning and Search Algorithms10.1007/978-3-030-72069-8_8(133-147)Online publication date: 29-Jul-2021
https://doi.org/10.1007/978-3-030-72069-8_8
Mishra SCoello C(2020)A parallel naive approach for non-dominated sorting: a theoretical study considering PRAM CREW modelSoft Computing10.1007/s00500-020-05450-1Online publication date: 26-Nov-2020
https://doi.org/10.1007/s00500-020-05450-1
Buzdalov MAuger AStützle T(2019)Generalized incremental orthant searchProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3319619.3326880(1357-1365)Online publication date: 13-Jul-2019
https://dl.acm.org/doi/10.1145/3319619.3326880
Mishra SCoello Coello C(2019)An Approach for Non-domination Level Update Problem in Steady-State Evolutionary Algorithms With Parallelism2019 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2019.8790072(1006-1013)Online publication date: Jun-2019
https://doi.org/10.1109/CEC.2019.8790072
Mishra SSaha SMondal SCoello C(2019)Divide-and-conquer based non-dominated sorting with Reduced ComparisonsSwarm and Evolutionary Computation10.1016/j.swevo.2019.100580(100580)Online publication date: Oct-2019
https://doi.org/10.1016/j.swevo.2019.100580
Yakupov IBuzdalov MTakadama K(2018)On asynchronous non-dominated sorting for steady-state multiobjective evolutionary algorithmsProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3205651.3205802(205-206)Online publication date: 6-Jul-2018
https://dl.acm.org/doi/10.1145/3205651.3205802
Buzdalov MTakadama K(2018)Generalized offline orthant searchProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205469(593-600)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3205455.3205469
Roy PDeb KIslam M(2018)An Efficient Nondominated Sorting Algorithm for Large Number of FrontsIEEE Transactions on Cybernetics10.1109/TCYB.2017.2789158(1-11)Online publication date: 2018
https://doi.org/10.1109/TCYB.2017.2789158
Mishra SCoello C(2018)P-ENS: Parallelism in Efficient Non-Dominated Sorting2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477948(1-8)Online publication date: Jul-2018
https://doi.org/10.1109/CEC.2018.8477948

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