スキーマを利用した自己組織化マップの重み更新則とその遺伝的アルゴリズムヘの応用(一般講演2A)

抄録

A Genetic Algorithm (GA) is a search algorithm based on the mechanics of natural selection and natural genetics. Searching in GA is achieved by iterating reproduction, crossover and mutation strategies. In these strategies, the reproduction strategy is the most important for deciding the searching points of the next generation. However, traditional reproduction operators may lose genetic diversity of population in an early stage, because they can not generate new chromosomes which are different from the present chromosomes. A decrease of genetic diversity leads to ineffectiveness of searching. We have proposed the reproduction strategy by utilizing an approximation ability of a binary version of a Self-Organizing Map to maintain the genetic diversity of the population. However, the searching performance is influenced by an ordering of inverting elements (bits) of a binary weight vector. In this paper, we propose a modified reproduction strategy with new updating rule of binarv weieht vectors based on schema.