Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs

Tetsuya Suzuki, Takehiro Tokuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In our metadata generation support system for landscape photographs, we use a genetic algorithm to find locations of photographs. Given a set of randomly generated solutions, the genetic algorithm tends to redundantly explore the search space because it is often that many worse solutions are distributed globally and a few better solutions are distributed locally in the search spaces of our search problems. To avoid such redundant searches, we propose a heuristic method to relocate worse solutions near better solutions before we execute the genetic algorithm. We show that the relocated initial solutions contribute to finding better solutions than randomly generated solutions by an experiment.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages67-74
Number of pages8
Volume4938 LNAI
DOIs
Publication statusPublished - 2008
Event3rd International Conference on Large-Scale Knowledge Resources, LKR 2008 - Tokyo
Duration: 2008 Mar 32008 Mar 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4938 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd International Conference on Large-Scale Knowledge Resources, LKR 2008
CityTokyo
Period08/3/308/3/5

Fingerprint

Metadata
Genetic algorithms
Heuristic methods

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Suzuki, T., & Tokuda, T. (2008). Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4938 LNAI, pp. 67-74). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4938 LNAI). https://doi.org/10.1007/978-3-540-78159-2_7

Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs. / Suzuki, Tetsuya; Tokuda, Takehiro.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4938 LNAI 2008. p. 67-74 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4938 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suzuki, T & Tokuda, T 2008, Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4938 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4938 LNAI, pp. 67-74, 3rd International Conference on Large-Scale Knowledge Resources, LKR 2008, Tokyo, 08/3/3. https://doi.org/10.1007/978-3-540-78159-2_7
Suzuki T, Tokuda T. Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4938 LNAI. 2008. p. 67-74. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-78159-2_7
Suzuki, Tetsuya ; Tokuda, Takehiro. / Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4938 LNAI 2008. pp. 67-74 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{d398e697d8e1414ca98a7e43032d2e46,
title = "Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs",
abstract = "In our metadata generation support system for landscape photographs, we use a genetic algorithm to find locations of photographs. Given a set of randomly generated solutions, the genetic algorithm tends to redundantly explore the search space because it is often that many worse solutions are distributed globally and a few better solutions are distributed locally in the search spaces of our search problems. To avoid such redundant searches, we propose a heuristic method to relocate worse solutions near better solutions before we execute the genetic algorithm. We show that the relocated initial solutions contribute to finding better solutions than randomly generated solutions by an experiment.",
author = "Tetsuya Suzuki and Takehiro Tokuda",
year = "2008",
doi = "10.1007/978-3-540-78159-2_7",
language = "English",
isbn = "3540781587",
volume = "4938 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "67--74",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Initial solution set improvement for a genetic algorithm in a metadata generation support system for landscape photographs

AU - Suzuki, Tetsuya

AU - Tokuda, Takehiro

PY - 2008

Y1 - 2008

N2 - In our metadata generation support system for landscape photographs, we use a genetic algorithm to find locations of photographs. Given a set of randomly generated solutions, the genetic algorithm tends to redundantly explore the search space because it is often that many worse solutions are distributed globally and a few better solutions are distributed locally in the search spaces of our search problems. To avoid such redundant searches, we propose a heuristic method to relocate worse solutions near better solutions before we execute the genetic algorithm. We show that the relocated initial solutions contribute to finding better solutions than randomly generated solutions by an experiment.

AB - In our metadata generation support system for landscape photographs, we use a genetic algorithm to find locations of photographs. Given a set of randomly generated solutions, the genetic algorithm tends to redundantly explore the search space because it is often that many worse solutions are distributed globally and a few better solutions are distributed locally in the search spaces of our search problems. To avoid such redundant searches, we propose a heuristic method to relocate worse solutions near better solutions before we execute the genetic algorithm. We show that the relocated initial solutions contribute to finding better solutions than randomly generated solutions by an experiment.

UR - http://www.scopus.com/inward/record.url?scp=40549108930&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=40549108930&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-78159-2_7

DO - 10.1007/978-3-540-78159-2_7

M3 - Conference contribution

AN - SCOPUS:40549108930

SN - 3540781587

SN - 9783540781585

VL - 4938 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 67

EP - 74

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -