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

Sousuke Tooyama, Hiroshi Hasegawa

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

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
Pages846-853
Number of pages8
DOIs
Publication statusPublished - 2009
Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim
Duration: 2009 May 182009 May 21

Other

Other2009 IEEE Congress on Evolutionary Computation, CEC 2009
CityTrondheim
Period09/5/1809/5/21

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Genetic algorithms
Genes
Evolutionary algorithms
Costs

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Tooyama, S., & Hasegawa, H. (2009). Adaptive plan system with genetic algorithm using the variable neighborhood range control. In 2009 IEEE Congress on Evolutionary Computation, CEC 2009 (pp. 846-853). [4983033] https://doi.org/10.1109/CEC.2009.4983033

Adaptive plan system with genetic algorithm using the variable neighborhood range control. / Tooyama, Sousuke; Hasegawa, Hiroshi.

2009 IEEE Congress on Evolutionary Computation, CEC 2009. 2009. p. 846-853 4983033.

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

Tooyama, S & Hasegawa, H 2009, Adaptive plan system with genetic algorithm using the variable neighborhood range control. in 2009 IEEE Congress on Evolutionary Computation, CEC 2009., 4983033, pp. 846-853, 2009 IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, 09/5/18. https://doi.org/10.1109/CEC.2009.4983033
Tooyama S, Hasegawa H. Adaptive plan system with genetic algorithm using the variable neighborhood range control. In 2009 IEEE Congress on Evolutionary Computation, CEC 2009. 2009. p. 846-853. 4983033 https://doi.org/10.1109/CEC.2009.4983033
Tooyama, Sousuke ; Hasegawa, Hiroshi. / Adaptive plan system with genetic algorithm using the variable neighborhood range control. 2009 IEEE Congress on Evolutionary Computation, CEC 2009. 2009. pp. 846-853
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