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A classification of dynamic multi-objective optimization problems

Authors:

Alexandru-Adrian Tantar,

Emilia Tantar,

Pascal BouvryAuthors Info & Claims

GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation

Pages 105 - 106

https://doi.org/10.1145/2001858.2001918

Published: 12 July 2011 Publication History

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Abstract

A classification of dynamic multi-objective optimization problems is proposed in this article. As compared to previous studies, we focus not on the changes or the effects that are induced in the Pareto optimal front or set but on the components that lead to the observed dynamic behaviour. Four main classes are identified, including parameter and function time-dependent evolution as well as state-dependent parameter and function transforms or environment changes.

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Cited By

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Hasan MLwin KShabut AHossain M(2019)Design and Development of a Benchmark for Dynamic Multi-objective Optimisation Problem in the Context of Deep Reinforcement Learning2019 22nd International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT48885.2019.9038529(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICCIT48885.2019.9038529
Hasan MAlam FChowdhury SKhan N(2019)Neural Machine Translation for the Bangla-English Language Pair2019 22nd International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT48885.2019.9038381(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICCIT48885.2019.9038381
Ding JYang CXiao QChai TJin Y(2018)Dynamic Evolutionary Multiobjective Optimization for Raw Ore Allocation in Mineral ProcessingIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2018.2812897(1-13)Online publication date: 2018
https://doi.org/10.1109/TETCI.2018.2812897
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A classification of dynamic multi-objective optimization problems
1. General and reference
  1. Document types
    1. Surveys and overviews

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Published In

GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation

July 2011

1548 pages

ISBN:9781450306904

DOI:10.1145/2001858

Editor:
Natalio Krasnogor
University of Nottingham, UK
,
General Chair:
Pier Luca Lanzi
Politecnico di Milano, Italy

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2011

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SIGEVO

GECCO '11: Genetic and Evolutionary Computation Conference

July 12 - 16, 2011

Dublin, Ireland

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

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Hasan MLwin KShabut AHossain M(2019)Design and Development of a Benchmark for Dynamic Multi-objective Optimisation Problem in the Context of Deep Reinforcement Learning2019 22nd International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT48885.2019.9038529(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICCIT48885.2019.9038529
Hasan MAlam FChowdhury SKhan N(2019)Neural Machine Translation for the Bangla-English Language Pair2019 22nd International Conference on Computer and Information Technology (ICCIT)10.1109/ICCIT48885.2019.9038381(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICCIT48885.2019.9038381
Ding JYang CXiao QChai TJin Y(2018)Dynamic Evolutionary Multiobjective Optimization for Raw Ore Allocation in Mineral ProcessingIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2018.2812897(1-13)Online publication date: 2018
https://doi.org/10.1109/TETCI.2018.2812897
Adrián Sosa Hernández VLara ATrautmann HRudolph GSchütze O(2016)The Directed Search Method for Unconstrained Parameter Dependent Multi-objective Optimization ProblemsNEO 201510.1007/978-3-319-44003-3_12(281-330)Online publication date: 24-Aug-2016
https://doi.org/10.1007/978-3-319-44003-3_12
Hernández VSchütze OTrautmann HRudolph G(2015)On the Behavior of Stochastic Local Search Within Parameter Dependent MOPsEvolutionary Multi-Criterion Optimization10.1007/978-3-319-15892-1_9(126-140)Online publication date: 18-Mar-2015
https://doi.org/10.1007/978-3-319-15892-1_9
Tantar ATantar EArnold D(2014)A survey on sustainability in ICTProceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation10.1145/2598394.2605695(1213-1220)Online publication date: 12-Jul-2014
https://dl.acm.org/doi/10.1145/2598394.2605695
Curtis SHancock BMattson C(2013)Usage scenarios for design space exploration with a dynamic multiobjective optimization formulationResearch in Engineering Design10.1007/s00163-013-0158-024:4(395-409)Online publication date: 24-Jul-2013
https://doi.org/10.1007/s00163-013-0158-0
Raquel CYao X(2013)Dynamic Multi-objective Optimization: A Survey of the State-of-the-ArtEvolutionary Computation for Dynamic Optimization Problems10.1007/978-3-642-38416-5_4(85-106)Online publication date: 2013
https://doi.org/10.1007/978-3-642-38416-5_4
McClymont KWalker DDupenois MMoore J(2012)The lay of the landProceedings of the 14th annual conference companion on Genetic and evolutionary computation10.1145/2330784.2330849(425-432)Online publication date: 7-Jul-2012
https://dl.acm.org/doi/10.1145/2330784.2330849

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Multi-objective Optimization with Dynamic Constraints and Objectives: New Challenges for Evolutionary Algorithms

A hybrid method for solving multi-objective global optimization problems

Evolving Dynamic Multi-Objective Optimization Problems with Objective Replacement

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