A Parameter Tuning Method Based on Meta-Heuristics for Genetic Algorithms

1 Citations 9 References

Bibliographic Information

Other Title
  • 遺伝的アルゴリズムに対するメタヒューリスティクスに基づくパラメータ値設定手法

Search this article

Description

Genetic algorithms (GA) are widely used to solve large-scaled optimization problems with complex constraints. GA has a powerful capability of exploring the search space of a given problem. However, since GA generally has many parameters, setting parameters for the problem instance is crucial for its performance. In this paper, we present an adaptive strategy, which selects a crossover operator to be used not in advance but dynamically during the execution. And we propose a new measure for adaptive operator selection, called elite degree. Elite degree shows the potential proficiency of an individual in the particular generation. Experimental results for benchmark test functions show the effectiveness of the proposed method.

Journal

  • IPSJ SIG Notes

    IPSJ SIG Notes 11 17-24, 1997-01-24

    Information Processing Society of Japan (IPSJ)

Citations (1)*help

See more

References(9)*help

See more

Details 詳細情報について

  • CRID
    1571980077130696064
  • NII Article ID
    110002936289
  • NII Book ID
    AN10505667
  • ISSN
    09196072
  • Text Lang
    ja
  • Data Source
    • CiNii Articles

Report a problem

Back to top