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

1 Citation (Scopus)

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 publicationLarge-Scale Knowledge Resources
Subtitle of host publicationConstruction and Application - Third International Conference on Large-Scale Knowledge Resources, LKR 2008, Proceedings
Pages67-74
Number of pages8
DOIs
Publication statusPublished - 2008 Mar 14
Event3rd International Conference on Large-Scale Knowledge Resources, LKR 2008 - Tokyo, Japan
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)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Large-Scale Knowledge Resources, LKR 2008
Country/TerritoryJapan
CityTokyo
Period08/3/308/3/5

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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