In a genetic algorithm (GA), the undesirable phenomenon of excess convergence can often occur. Excess convergence is the phenomenon where the diversity of a group is lost. This phenomenon occurs because homogeneous individuals are increased rapidly in the group while searching, Therefore, a crossover loses its function. Once the excess convergence occurs, the search by the GA becomes meaningless. It then becomes important in the adaptation of the GA to avoid this excess convergence and maintain the diversity. First, we show an implementation of a parallel GA based on a multiple group type island model by using object-shared space. Next, as an effective method for avoiding the excess convergence in a simple mechanism, we propose the diversity maintenance technique based on selection of the homogeneous individuals called Noah's ark strategy in parallel GA, and clarify the effectiveness on the knapsack problem. Our proposed method is to replace the individuals of sub-groups having the excess convergence with the new individual coming from the search space. That is avoid the excess convergence by expelling homogeneous individuals asynchronously except for Noah who is an elite individual, and limiting a decrease of the diversity of the entire sub-group.
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