Adaptive plan system with genetic algorithm using the variable neighborhood range control

Sousuke Tooyama, Hiroshi Hasegawa

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

To improve the calculation cost and the convergence to optimal solutions for multi-peak optimization problems with multiple dimensions, we propose a new evolutionary algorithm, which is an Adaptive Plan system with Genetic Algorithm (APGA). This is an approach that combines the global search ability of a GA and an Adaptive Plan with excellent local search ability. The APGA differs from GAs in how it handles design variable vectors. GAs generally encode design variable vectors into genes, and handle them through GA operations. However, the APGA encodes the control variable vectors of the Adaptive Plan, which searches for local minima, into its genes. The control variable vectors determine the global behavior of the AP, and design variable vectors are handled by the AP in the optimization process of the APGA. In this paper, the Variable Neighborhood range Control (VNC), which changes a neighborhood range based on an individual's situation-fitness, is introduced into the APGA to dramatically improve the convergence up to the optimal solution. The APGA/VNC is applied to some benchmark functions to evaluate its performance. We confirmed satisfactory performancethrough these various benchmark tests.

本文言語English
ホスト出版物のタイトル2009 IEEE Congress on Evolutionary Computation, CEC 2009
ページ846-853
ページ数8
DOI
出版ステータスPublished - 2009 11 26
イベント2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
継続期間: 2009 5 182009 5 21

出版物シリーズ

名前2009 IEEE Congress on Evolutionary Computation, CEC 2009

Conference

Conference2009 IEEE Congress on Evolutionary Computation, CEC 2009
国/地域Norway
CityTrondheim
Period09/5/1809/5/21

ASJC Scopus subject areas

  • 人工知能
  • 計算理論と計算数学
  • 理論的コンピュータサイエンス

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