TY - GEN
T1 - A visualization of genetic algorithm using the pseudo-color
AU - Ito, Shin Ichi
AU - Mitsukura, Yasue
AU - Miyamura, Hiroko Nakamura
AU - Saito, Takafumi
AU - Fukumi, Minoru
PY - 2008/10/23
Y1 - 2008/10/23
N2 - 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.
AB - 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.
KW - Binary-coded genetic algorithm
KW - Pseudo-color
KW - Visualization
KW - Zero-one knapsack problem
UR - http://www.scopus.com/inward/record.url?scp=54049098386&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=54049098386&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-69162-4_46
DO - 10.1007/978-3-540-69162-4_46
M3 - Conference contribution
AN - SCOPUS:54049098386
SN - 3540691596
SN - 9783540691594
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 444
EP - 452
BT - Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
T2 - 14th International Conference on Neural Information Processing, ICONIP 2007
Y2 - 13 November 2007 through 16 November 2007
ER -