A benchmark generator of tree decomposition Mk landscapes

Dirk Thierens; Tobias Driessel, van

doi:10.1145/3449726.3459427

A benchmark generator of tree decomposition Mk landscapes

Dirk Thierens, Tobias Driessel, van

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

Abstract

We introduce the CliqueTreeMk algorithm to construct tree decomposition (TD) Mk Landscapes and to compute their global optimum efficiently. TD Mk Landscapes are well suited to serve as benchmark functions for blackbox genetic algorithms that are not given a priori the structural problem information as specified by the tree structure and their associated codomain fitness values. Specifically, for certain types of codomains the use of linkage learning might prove to be necessary in order to be able to solve these type of fitness functions.

Original language	English
Title of host publication	Proceedings of the Genetic and Evolutionary Computation Conference
Editors	Francisco Chicano, Krzysztof Krawiec
Publisher	Association for Computing Machinery
Pages	229-230
ISBN (Print)	978-1-4503-8350-9
DOIs	https://doi.org/10.1145/3449726.3459427
Publication status	Published - Jul 2021
Event	Genetic and Evolutionary Computation Conference - Duration: 10 Jul 2021 → 14 Jul 2021

Conference

Conference	Genetic and Evolutionary Computation Conference
Period	10/07/21 → 14/07/21

Keywords

Benchmarking
Decomposable Landscapes
Dynamic Programming

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10.1145/3449726.3459427

3449726.3459427Final published version, 574 KBLicence: Taverne

Cite this

@inproceedings{b57cf561c2ca49b58704e912eee754ec,

title = "A benchmark generator of tree decomposition Mk landscapes",

abstract = "We introduce the CliqueTreeMk algorithm to construct tree decomposition (TD) Mk Landscapes and to compute their global optimum efficiently. TD Mk Landscapes are well suited to serve as benchmark functions for blackbox genetic algorithms that are not given a priori the structural problem information as specified by the tree structure and their associated codomain fitness values. Specifically, for certain types of codomains the use of linkage learning might prove to be necessary in order to be able to solve these type of fitness functions.",

keywords = "Benchmarking, Decomposable Landscapes, Dynamic Programming",

author = "Dirk Thierens and {Driessel, van}, Tobias",

year = "2021",

month = jul,

doi = "10.1145/3449726.3459427",

language = "English",

isbn = "978-1-4503-8350-9",

pages = "229--230",

editor = "Francisco Chicano and Krzysztof Krawiec",

booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference",

publisher = "Association for Computing Machinery",

address = "United States",

note = "Genetic and Evolutionary Computation Conference ; Conference date: 10-07-2021 Through 14-07-2021",

}

A benchmark generator of tree decomposition Mk landscapes. / Thierens, Dirk; Driessel, van, Tobias.
Proceedings of the Genetic and Evolutionary Computation Conference. ed. / Francisco Chicano; Krzysztof Krawiec. Association for Computing Machinery, 2021. p. 229-230.

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

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N2 - We introduce the CliqueTreeMk algorithm to construct tree decomposition (TD) Mk Landscapes and to compute their global optimum efficiently. TD Mk Landscapes are well suited to serve as benchmark functions for blackbox genetic algorithms that are not given a priori the structural problem information as specified by the tree structure and their associated codomain fitness values. Specifically, for certain types of codomains the use of linkage learning might prove to be necessary in order to be able to solve these type of fitness functions.

AB - We introduce the CliqueTreeMk algorithm to construct tree decomposition (TD) Mk Landscapes and to compute their global optimum efficiently. TD Mk Landscapes are well suited to serve as benchmark functions for blackbox genetic algorithms that are not given a priori the structural problem information as specified by the tree structure and their associated codomain fitness values. Specifically, for certain types of codomains the use of linkage learning might prove to be necessary in order to be able to solve these type of fitness functions.

KW - Benchmarking

KW - Decomposable Landscapes

KW - Dynamic Programming

U2 - 10.1145/3449726.3459427

DO - 10.1145/3449726.3459427

M3 - Conference contribution

SN - 978-1-4503-8350-9

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EP - 230

BT - Proceedings of the Genetic and Evolutionary Computation Conference

A2 - Chicano, Francisco

A2 - Krawiec, Krzysztof

PB - Association for Computing Machinery

T2 - Genetic and Evolutionary Computation Conference

Y2 - 10 July 2021 through 14 July 2021

ER -

A benchmark generator of tree decomposition Mk landscapes

Abstract

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Keywords

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