Real-coded GA for High-dimensional k-tablet Structures: Proposal and Evaluation of Latent Variable Crossover LUNDX-m

DOI Web Site Web Site 9 Citations 19 References

Bibliographic Information

Other Title
  • 高次元ｋ‐ｔａｂｌｅｔ構造を考慮した実数値ＧＡ　　隠れ変数上の交叉ＬＵＮＤＸ‐ｍの提案と評価
  • 高次元k-tablet構造を考慮した実数値GA--隠れ変数上の交叉LUNDX-mの提案と評価
  • コウジゲン k tablet コウゾウ オ コウリョ シタ ジッスウチ GA カクレ ヘンスウ ジョウ ノ コウサ LUNDX m ノ テイアン ト ヒョウカ
  • Proposal and Evaluation of Latent Variable Crossover LUNDX-<I>m</I>
  • 隠れ変数上の交叉LUNDX-<I>m</I>の提案と評価

Search this article

Abstract

This paper presents the Real-coded Genetic Algorithms(RCGA) which can treat with high-dimensional ill-scaled structures, what is called, k-tablet structure. The k-tablet structure is the landscape that the scale of the fitness function is different between the k-dimensional subspace and the orthogonal (n-k)-dimensional subspace. The search speed of traditional RCGAs degrades when high-dimensional k-tablet structures are included in the landscape of fitness function. <P> In this structure, offspring generated by crossovers is likely to spread wider region than the region where the parental population covers. This phenomenon causes the stagnation of the search. To resolve this problem, we propose a new crossover LUNDX-m, which uses only m-dimensional latent variables. The effectiveness of the proposal method is tested with several benchmark functions including k-tablet structures and we show that our proposal method performs better than traditional crossovers especially when the dimensionality n is higher than 100.

Journal

Citations (9)*help

See more

References(19)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top