An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems

Zhun Fan; Hui Li; Caimin Wei; Wenji Li; Han Huang; Xinye Cai; Zhaoquan Cai

doi:10.1109/SSCI.2016.7850224

An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems

Zhun Fan
, Hui Li
, Caimin Wei
, Wenji Li
, Han Huang
, Xinye Cai
, Zhaoquan Cai

School of Mathematics and Statistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

82 Scopus citations

Abstract

This paper proposes an improved epsilon constraint handling method embedded in the multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve constrained multi-objective optimization problems (CMOPs). More specifically, it dynamically adjusts the epsilon level, which is a critical parameter in the epsilon constraint method, according to the feasible ratio of solutions in the current population. In order to verify the effect of the improved epsilon constraint handling method, three algorithms - MOEA/D-CDP, MOEA/D-Epsilon, and MOEA/D-IEpsilon (MOEA/D with the improved epsilon constraint handling mechanism) are tested on nine CMOPs (CMOP1-CMOP9). The comprehensive experimental results indicate that the proposed epsilon constraint handling method is very effective on the performance of both convergence and diversity.

Original language	English
Title of host publication	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509042401
DOIs	https://doi.org/10.1109/SSCI.2016.7850224
State	Published - 9 Feb 2017
Event	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 - Athens, Greece Duration: 6 Dec 2016 → 9 Dec 2016

Publication series

Name	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

Conference

Conference	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Country/Territory	Greece
City	Athens
Period	6/12/16 → 9/12/16

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10.1109/SSCI.2016.7850224

Cite this

Fan, Z., Li, H., Wei, C., Li, W., Huang, H., Cai, X., & Cai, Z. (2017). An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 Article 7850224 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2016.7850224

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title = "An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems",

abstract = "This paper proposes an improved epsilon constraint handling method embedded in the multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve constrained multi-objective optimization problems (CMOPs). More specifically, it dynamically adjusts the epsilon level, which is a critical parameter in the epsilon constraint method, according to the feasible ratio of solutions in the current population. In order to verify the effect of the improved epsilon constraint handling method, three algorithms - MOEA/D-CDP, MOEA/D-Epsilon, and MOEA/D-IEpsilon (MOEA/D with the improved epsilon constraint handling mechanism) are tested on nine CMOPs (CMOP1-CMOP9). The comprehensive experimental results indicate that the proposed epsilon constraint handling method is very effective on the performance of both convergence and diversity.",

author = "Zhun Fan and Hui Li and Caimin Wei and Wenji Li and Han Huang and Xinye Cai and Zhaoquan Cai",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 ; Conference date: 06-12-2016 Through 09-12-2016",

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doi = "10.1109/SSCI.2016.7850224",

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Fan, Z, Li, H, Wei, C, Li, W, Huang, H, Cai, X & Cai, Z 2017, An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems. in 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016., 7850224, 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, Athens, Greece, 6/12/16. https://doi.org/10.1109/SSCI.2016.7850224

An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems. / Fan, Zhun; Li, Hui; Wei, Caimin et al.
2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7850224 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Fan, Zhun

AU - Li, Hui

AU - Wei, Caimin

AU - Li, Wenji

AU - Huang, Han

AU - Cai, Xinye

AU - Cai, Zhaoquan

PY - 2017/2/9

Y1 - 2017/2/9

N2 - This paper proposes an improved epsilon constraint handling method embedded in the multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve constrained multi-objective optimization problems (CMOPs). More specifically, it dynamically adjusts the epsilon level, which is a critical parameter in the epsilon constraint method, according to the feasible ratio of solutions in the current population. In order to verify the effect of the improved epsilon constraint handling method, three algorithms - MOEA/D-CDP, MOEA/D-Epsilon, and MOEA/D-IEpsilon (MOEA/D with the improved epsilon constraint handling mechanism) are tested on nine CMOPs (CMOP1-CMOP9). The comprehensive experimental results indicate that the proposed epsilon constraint handling method is very effective on the performance of both convergence and diversity.

AB - This paper proposes an improved epsilon constraint handling method embedded in the multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve constrained multi-objective optimization problems (CMOPs). More specifically, it dynamically adjusts the epsilon level, which is a critical parameter in the epsilon constraint method, according to the feasible ratio of solutions in the current population. In order to verify the effect of the improved epsilon constraint handling method, three algorithms - MOEA/D-CDP, MOEA/D-Epsilon, and MOEA/D-IEpsilon (MOEA/D with the improved epsilon constraint handling mechanism) are tested on nine CMOPs (CMOP1-CMOP9). The comprehensive experimental results indicate that the proposed epsilon constraint handling method is very effective on the performance of both convergence and diversity.

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Fan Z, Li H, Wei C, Li W, Huang H, Cai X et al. An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7850224. (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). doi: 10.1109/SSCI.2016.7850224

An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems

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