Spread assessment for evolutionary multi-objective optimization

Miqing Li; Jinhua Zheng

doi:10.1007/978-3-642-01020-0_20

Spread assessment for evolutionary multi-objective optimization

Miqing Li^*, Jinhua Zheng

^*Corresponding author for this work

Computer Science

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

42 Citations (Scopus)

Abstract

Convergence, uniformity and spread are three basic issues in comparing the performance of multi-objective evolutionary algorithms. However, most of metrics pay more attention on former two performance indices. In this paper, we introduce a metric for evaluating the spread of non-dominated solutions. Unlike existed metrics only calculating the extreme solutions in objective space, this metric defines boundary concept of non-dominated set. And it evaluates the extent of boundary solutions by projecting them on low-dimensional spaces. Moreover, the centroid of solutions set is introduced to avoid the impact of different convergence result of algorithms. From a comparative study on several test problems, the metric is examined to assess spread of non-dominated solutions set in objective space.

Original language	English
Title of host publication	Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings
Pages	216-230
Number of pages	15
DOIs	https://doi.org/10.1007/978-3-642-01020-0_20
Publication status	Published - 2010
Event	5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009 - Nantes, France Duration: 7 Apr 2009 → 10 Apr 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5467 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009
Country/Territory	France
City	Nantes
Period	7/04/09 → 10/04/09

Keywords

Boundary solution
Hypervolume
Multi-objective optimization
Performance assessment
Spread

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-01020-0_20

Cite this

Li, M., & Zheng, J. (2010). Spread assessment for evolutionary multi-objective optimization. In Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings (pp. 216-230). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5467 LNCS). https://doi.org/10.1007/978-3-642-01020-0_20

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title = "Spread assessment for evolutionary multi-objective optimization",

abstract = "Convergence, uniformity and spread are three basic issues in comparing the performance of multi-objective evolutionary algorithms. However, most of metrics pay more attention on former two performance indices. In this paper, we introduce a metric for evaluating the spread of non-dominated solutions. Unlike existed metrics only calculating the extreme solutions in objective space, this metric defines boundary concept of non-dominated set. And it evaluates the extent of boundary solutions by projecting them on low-dimensional spaces. Moreover, the centroid of solutions set is introduced to avoid the impact of different convergence result of algorithms. From a comparative study on several test problems, the metric is examined to assess spread of non-dominated solutions set in objective space.",

keywords = "Boundary solution, Hypervolume, Multi-objective optimization, Performance assessment, Spread",

author = "Miqing Li and Jinhua Zheng",

year = "2010",

doi = "10.1007/978-3-642-01020-0_20",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Li, M & Zheng, J 2010, Spread assessment for evolutionary multi-objective optimization. in Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5467 LNCS, pp. 216-230, 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009, Nantes, France, 7/04/09. https://doi.org/10.1007/978-3-642-01020-0_20

Spread assessment for evolutionary multi-objective optimization. / Li, Miqing; Zheng, Jinhua.
Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings. 2010. p. 216-230 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5467 LNCS).

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

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AU - Zheng, Jinhua

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AB - Convergence, uniformity and spread are three basic issues in comparing the performance of multi-objective evolutionary algorithms. However, most of metrics pay more attention on former two performance indices. In this paper, we introduce a metric for evaluating the spread of non-dominated solutions. Unlike existed metrics only calculating the extreme solutions in objective space, this metric defines boundary concept of non-dominated set. And it evaluates the extent of boundary solutions by projecting them on low-dimensional spaces. Moreover, the centroid of solutions set is introduced to avoid the impact of different convergence result of algorithms. From a comparative study on several test problems, the metric is examined to assess spread of non-dominated solutions set in objective space.

KW - Boundary solution

KW - Hypervolume

KW - Multi-objective optimization

KW - Performance assessment

KW - Spread

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SN - 9783642010194

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BT - Evolutionary Multi-Criterion Optimization - 5th International Conference, EMO 2009, Proceedings

T2 - 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009

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ER -

Spread assessment for evolutionary multi-objective optimization

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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