Abstract
GA searches neighborhood of the genes that have high evaluation values as it is assumed that neighboring relationship of individuals in the genotype space is similar to that in the evaluation space. However, it is difficult to decide which coding, deciding the similarity between them, and which genetic operation to use because there is no criterion for the similarity and the landscape of search space. As a result, they are decided by trial and error in a lot of cases. This paper proposes the visualization method to grasp the relationship between genes and their evaluation values for efficient search. This paper applies the proposed method to a benchmark function of multi-objective optimization problem and shows that it enables us to grasp the similarity of genes between in the genotype space and evaluation space. It also shows that we could feed back the visualization result to genetic operations for more efficient search.
