A visualization of genetic algorithm using the pseudo-color

Shin Ichi Ito, Yasue Mitsukura, Hiroko Nakamura Miyamura, Takafumi Saito, Minoru Fukumi

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

10 Citations (Scopus)


In this paper, we propose a visualization method to grasp the search process and results in the binary-coded genetic algorithm. The representation, the choices of operations, and the associated parameters can each make a major difference to the speed and the quality of the final result. These parameters are decided interactively and very difficult to disentangle their effects. Therefore, we focus on the chromosome structure, the fitness function, the objective function, the termination conditions, and the association among these parameters. We can indicate the most important or optimum parameters in visually. The proposed method is indicated all individuals of the current generation using the pseudo-color. The pixels related a gene of the chromosome are painted the red color when the gene of the chromosome represents '1', and the pixels related to one are painted the blue color when one represents '0'. Then the brightness of the chromosome changes by the fitness value, and the hue of the chromosome changes by the objective value. In order to show the effectiveness of the proposed method, we apply the proposed method to the zero-one knapsack problems.

Original languageEnglish
Title of host publicationNeural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
Number of pages9
EditionPART 2
Publication statusPublished - 2008 Oct 23
Externally publishedYes
Event14th International Conference on Neural Information Processing, ICONIP 2007 - Kitakyushu, Japan
Duration: 2007 Nov 132007 Nov 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume4985 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other14th International Conference on Neural Information Processing, ICONIP 2007


  • Binary-coded genetic algorithm
  • Pseudo-color
  • Visualization
  • Zero-one knapsack problem

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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