Development of Multi-stage and Hybrid Real-coded Genetic Algorithms with Active Constraints

In this study, we propose multi-stage and hybrid real-coded genetic algorithm. In the proposed algorithm, there are two stages. In the first stage, Real-coded Genetic Algorithm with Active Constraints (RGAAC) is applied to find a solution that is close to the global optimum. In RGAAC, individuals who are out of the feasible region are pulled back into feasible region. Therefore, the effective search can be carried out even in the constraints problems. In the second stage, Feasible Region Limiting Method (FRLM) is applied to obtain an optimum solution. FRLM uses the solution that is derived in the first stage as an initial point. In this study, RGAAC is applied to solve the truss structure problems. Through these problems, the effectiveness and the searching mechanism of RGAAC is discussed. Then, the proposed algorithm is also applied to 2D problem. In this problem, there are about 1000 design variables. The proposed method can derive the reasonable solution. From these results, it is concluded that the proposed method is effective to solve optimization problems of large-scale structures. mura @garlic.q.t.u-tokyo.ac.jp o @is.doshisha.ac.jp