A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis

Maciej Komosinski; Agnieszka Mensfelt

doi:10.1007/978-3-030-16692-2_8

A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis

Department of Computer Science

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

Original language	English
Title of host publication	Applications of Evolutionary Computation
Subtitle of host publication	22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings
Editors	Paul Kaufmann, Pedro A. Castillo
Publisher	Springer, [Cham]
Pages	106-121
Number of pages	16
ISBN (Print)	9783030166915
DOIs	https://doi.org/10.1007/978-3-030-16692-2_8
Publication status	Published - 30 Mar 2019
Event	22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019 - Leipzig, Germany Duration: 24 Apr 2019 → 26 Apr 2019

Publication series

Name	Lecture Notes in Computer Science
Volume	11454 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019
Country/Territory	Germany
City	Leipzig
Period	24/04/19 → 26/04/19

Keywords

3D structure
Dissimilarity measure
Evolutionary design
Global convexity
Optimization

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10.1007/978-3-030-16692-2_8

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Komosinski, M., & Mensfelt, A. (2019). A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 106-121). (Lecture Notes in Computer Science; Vol. 11454 LNCS). Springer, [Cham]. https://doi.org/10.1007/978-3-030-16692-2_8

Komosinski, Maciej ; Mensfelt, Agnieszka. / A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis. Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings. editor / Paul Kaufmann ; Pedro A. Castillo. Springer, [Cham], 2019. pp. 106-121 (Lecture Notes in Computer Science).

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Komosinski, M & Mensfelt, A 2019, A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis. in P Kaufmann & PA Castillo (eds), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings. Lecture Notes in Computer Science, vol. 11454 LNCS, Springer, [Cham], pp. 106-121, 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019, Leipzig, Germany, 24/04/19. https://doi.org/10.1007/978-3-030-16692-2_8

A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis. / Komosinski, Maciej; Mensfelt, Agnieszka.
Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings. ed. / Paul Kaufmann; Pedro A. Castillo. Springer, [Cham], 2019. p. 106-121 (Lecture Notes in Computer Science; Vol. 11454 LNCS).

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

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KW - Global convexity

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Komosinski M, Mensfelt A. A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis. In Kaufmann P, Castillo PA, editors, Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings. Springer, [Cham]. 2019. p. 106-121. (Lecture Notes in Computer Science). doi: 10.1007/978-3-030-16692-2_8

A flexible dissimilarity measure for active and passive 3D structures and its application in the fitness–distance analysis

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Keywords

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