Adjusting parallel coordinates for investigating multi-objective search

Liangli ZHEN*, Miqing LI, Ran CHENG, Dezhong PENG, Xin YAO

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

12 Citations (Scopus)


Visualizing a high-dimensional solution set over the evolution process is a viable way to investigate the search behavior of evolutionary multi-objective optimization. The parallel coordinates plot which scales well to the data dimensionality is frequently used to observe solution sets in multi-objective optimization. However, the solution sets in parallel coordinates are typically presented by the natural order of the optimized objectives, with rare information of the relation between these objectives and also the Pareto dominance relation between solutions. In this paper, we attempt to adjust parallel coordinates to incorporate this information. Systematic experiments have shown the effectiveness of the proposed method. © Springer International Publishing AG 2017.
Original languageEnglish
Title of host publicationSimulated Evolution and Learning : 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings
EditorsYuhui SHI, Kay Chen TAN, Mengjie ZHANG, Ke TANG, Xiaodong LI, Qingfu ZHANG, Ying TAN, Martin MIDDENDORF, Yaochu JIN
Number of pages12
ISBN (Electronic)9783319687599
ISBN (Print)9783319687582
Publication statusPublished - 2017
Externally publishedYes
Event11th International Conference on Simulated Evolution and Learning, SEAL 2017 - Shenzhen, China
Duration: 10 Nov 201713 Nov 2017

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameTheoretical Computer Science and General Issues
ISSN (Print)2512-2010
ISSN (Electronic)2512-2029


Conference11th International Conference on Simulated Evolution and Learning, SEAL 2017
Abbreviated titleSEAL 2017

Bibliographical note

This work was supported in part by the National Natural Science Foundation of China under grants 61432012, 61329302, and the Engineering and Physical Sciences Research Council (EPSRC) of UK under grant EP/J017515/1.


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