Genetic Algorithms (GAs) are the models of biological evolution. But the concept of degeneration had not been introduced to GA. Degeneration is the evolutionary decline or loss of a function or characteristic. So, it had not been thought that degeneration could be used for optimization.
In this paper, GA with degeneration (GAd) that introduces the concept of degeneration to GA is proposed.
It is  assumed that the damaged genes and irreversible mutations cause the degeneration.
If degeneration occurred, some characteristics of an individual were lost.
If the characteristics are regarded as parameters in a model, the parameters can be reduced and the optimal parameter structure can be discovered. It is shown that the optimal parameter structure of some models such as neural networks can be discovered by GAd.