结合序列线性规划法的混合遗传算法

通过将遗传算法与改进的序列线性规划法相结合，形成混合遗传算法．当迭代点没有发生交叉和变异时，将目标函数和约束条件在迭代点处线性化，为使迭代点邻域仍然满足约束条件，加入软约束项，用线性规划方法进行寻优．该方法具有全局收敛性，不要求迭代点一定为可行点．仿真结果验证了此法的有效性和合理性．

A Hybrid Genetic Algorithm Integrated with Sequential Linear Programming

A new hybrid genetic algorithm is proposed for nonlinear programming problems in this paper, which combines genetic algorithm ( GA) with sequential linear programming method. During the iterative computation process, if crossover or mutation operation don' t happen at the iterative points in the GA, the objective function and constraints at these points will be linearized. In order to satisfy the constraints within the neighborhood of these points, this paper considers adding soft constraints, and the linearized optimization problem can be solved with the linear programming. The new hybrid genetic algorithm is globally convergent; it does not require that the iterative points must be feasible. Simulation results show that the algorithm is effective and reasonable.