書誌事項
- タイトル別名
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- Selection of Initial Solutions for Local Search in Multiobjective Genetic Local Search
- タモクテキ イデンテキ キョクショ タンサク アルゴリズム ニ オケル キョクショ タンサク テキヨウ コタイ ノ センタク
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In this paper, we propose a new selection scheme of initial solutions for the local search of a multiobjective genetic local search (MOGLS) algorithm. The MOGLS algorithm is the hybridization of an evolutionary multiobjective optimization (EMO) algorithm and local search. It is shown that the MOGLS algorithm has higher search ability than pure EMO algorithms. In the conventional MOGLS algorithm, the local search method is applied to the offspring population generated by the genetic operators. However, the generated offspring population often includes poor individuals because the genetic operators involve some random procedures and allow the generation of inferior offspring. The basic idea of our approach is to apply local search to the parent population. Thus our approach can apply local search to better solutions than the original MOGLS algorithm on average. Through computational experiments, we show that our approach improves the search ability of the MOGLS algorithm. <br>
収録刊行物
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- システム制御情報学会論文誌
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システム制御情報学会論文誌 23 (8), 178-187, 2010
一般社団法人 システム制御情報学会
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詳細情報 詳細情報について
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- CRID
- 1390001205165058304
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- NII論文ID
- 10027615260
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- NII書誌ID
- AN1013280X
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- ISSN
- 2185811X
- 13425668
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- NDL書誌ID
- 10781118
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可