EGA

alpha

A novel and effictive GA algorithm to solve optimization problem

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Description

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and.
Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.

EGA Web Site

Features

  • cluser
  • ap
  • ga

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User Reviews

  • maxgarcia
    1 of 5 2 of 5 3 of 5 4 of 5 5 of 5

    Fast and simple.

    Posted 01/21/2013
  • nolanromero
    1 of 5 2 of 5 3 of 5 4 of 5 5 of 5

    good work

    Posted 12/20/2012
  • maxcox
    1 of 5 2 of 5 3 of 5 4 of 5 5 of 5

    Reliable and runs smoothly

    Posted 11/07/2012
  • leolopez
    1 of 5 2 of 5 3 of 5 4 of 5 5 of 5

    Nice and simple.

    Posted 09/17/2012
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Additional Project Details

Languages

Chinese (Simplified), English

Intended Audience

Engineering, Government, Architects

User Interface

Eclipse

Programming Language

Java

Registered

2011-12-27
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