On Analysis of Irregular Pareto Front Shapes

Shouyong Jiang; Jinglei Guo; Bashar Alhnaity; Qingyang Zhang

doi:10.1007/978-3-030-72062-9_2

On Analysis of Irregular Pareto Front Shapes

Shouyong Jiang^*, Jinglei Guo, Bashar Alhnaity, Qingyang Zhang

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

2 Citations (Scopus)

Abstract

After decades of effort, evolutionary algorithms have been able to solve a variety of multiobjective optimisation problems with diverse characteristics. However, the presence of irregularity in the Pareto-optimal front is increasingly recognised as a big challenge to some well-established algorithms. In order to further our understanding of this irregularity and its effect on algorithms, we develop a generic framework of constructing irregular Pareto-optimal front shapes, and use it as a tool to examine the performance of some well-known algorithms. Experimental results reveal that conventional algorithms are not always inferior to the state of the arts, and all the algorithms considered in this paper face some unexpected challenges when dealing with irregularity of Pareto-optimal front. The findings suggest that a systematic evaluation and analysis is needed for any newly-developed algorithms to avoid biases.

Original language	English
Title of host publication	Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings
Editors	Hisao Ishibuchi, Qingfu Zhang, Ran Cheng, Ke Li, Hui Li, Handing Wang, Aimin Zhou
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	15-25
Number of pages	11
ISBN (Print)	9783030720612
DOIs	https://doi.org/10.1007/978-3-030-72062-9_2
Publication status	Published - 2021
Event	11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021 - Shenzhen, China Duration: 28 Mar 2021 → 31 Mar 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12654 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021
Country/Territory	China
City	Shenzhen
Period	28/03/21 → 31/03/21

Bibliographical note

Funding Information:
Acknowledgements. This work was supported by National Natural Science Foundation of China (Grant No. 62006103).

Keywords

Evolutionary algorithm
Irregular Pareto front
Multi-objective optimization
Test problem

Access to Document

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Cite this

Jiang, S., Guo, J., Alhnaity, B., & Zhang, Q. (2021). On Analysis of Irregular Pareto Front Shapes. In H. Ishibuchi, Q. Zhang, R. Cheng, K. Li, H. Li, H. Wang, & A. Zhou (Eds.), Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings (pp. 15-25). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12654 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-72062-9_2

On Analysis of Irregular Pareto Front Shapes. / Jiang, Shouyong; Guo, Jinglei; Alhnaity, Bashar et al.
Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings. ed. / Hisao Ishibuchi; Qingfu Zhang; Ran Cheng; Ke Li; Hui Li; Handing Wang; Aimin Zhou. Springer Science and Business Media Deutschland GmbH, 2021. p. 15-25 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12654 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Jiang, S, Guo, J, Alhnaity, B & Zhang, Q 2021, On Analysis of Irregular Pareto Front Shapes. in H Ishibuchi, Q Zhang, R Cheng, K Li, H Li, H Wang & A Zhou (eds), Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12654 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 15-25, 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021, Shenzhen, China, 28/03/21. https://doi.org/10.1007/978-3-030-72062-9_2

Jiang S, Guo J, Alhnaity B, Zhang Q. On Analysis of Irregular Pareto Front Shapes. In Ishibuchi H, Zhang Q, Cheng R, Li K, Li H, Wang H, Zhou A, editors, Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 15-25. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Mar 24. doi: 10.1007/978-3-030-72062-9_2

Jiang, Shouyong ; Guo, Jinglei ; Alhnaity, Bashar et al. / On Analysis of Irregular Pareto Front Shapes. Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Proceedings. editor / Hisao Ishibuchi ; Qingfu Zhang ; Ran Cheng ; Ke Li ; Hui Li ; Handing Wang ; Aimin Zhou. Springer Science and Business Media Deutschland GmbH, 2021. pp. 15-25 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "After decades of effort, evolutionary algorithms have been able to solve a variety of multiobjective optimisation problems with diverse characteristics. However, the presence of irregularity in the Pareto-optimal front is increasingly recognised as a big challenge to some well-established algorithms. In order to further our understanding of this irregularity and its effect on algorithms, we develop a generic framework of constructing irregular Pareto-optimal front shapes, and use it as a tool to examine the performance of some well-known algorithms. Experimental results reveal that conventional algorithms are not always inferior to the state of the arts, and all the algorithms considered in this paper face some unexpected challenges when dealing with irregularity of Pareto-optimal front. The findings suggest that a systematic evaluation and analysis is needed for any newly-developed algorithms to avoid biases.",

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AU - Guo, Jinglei

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Y1 - 2021

N2 - After decades of effort, evolutionary algorithms have been able to solve a variety of multiobjective optimisation problems with diverse characteristics. However, the presence of irregularity in the Pareto-optimal front is increasingly recognised as a big challenge to some well-established algorithms. In order to further our understanding of this irregularity and its effect on algorithms, we develop a generic framework of constructing irregular Pareto-optimal front shapes, and use it as a tool to examine the performance of some well-known algorithms. Experimental results reveal that conventional algorithms are not always inferior to the state of the arts, and all the algorithms considered in this paper face some unexpected challenges when dealing with irregularity of Pareto-optimal front. The findings suggest that a systematic evaluation and analysis is needed for any newly-developed algorithms to avoid biases.

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On Analysis of Irregular Pareto Front Shapes

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Keywords

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