Genetic algorithm with age structure and its application to self-organizing manufacturing system

The genetic algorithm has recently been demonstrated its effectiveness in optimization issues, but it has two major problems: a premature local convergence and a bias by the genetic drift. In order to solve these problems, we propose a new genetic algorithm with an age structure of a continuous generation model. The new genetic algorithm is applied to a self-organizing manufacturing system-a process which self-organizes to other processes in a flexible manufacturing system environment. The effectiveness of the genetic algorithm with age structure is demonstrated through numerical simulations of the reorganization of a press machining line as an example of the self-organizing manufacturing system.<>