基于分层遗传算法的一类非线性规划问题的新解法

关于非线性规划的问题的诸多传统解法中都存在效率较低、容易达到局部最优、甚至找不到最优解的局限性。而基本遗传算法也常常由于本身算法的局限性,在搜索最优解的过程中易早熟,局部搜索能力弱,后期收敛过慢。源于这些缺陷,本论文提出使用分层遗传算法来求解一类非线性规划问题,并通过数值实验,结果表明基于分层遗传算法求解一类非线性规划问题是非常有效的。

New Algorithm for a Class of Nonlinear Programming Problem Based on Hierarchical Genetic Algorithm

The traditional method of nonlinear programming problems is low efficiency,easy to achieve local optimum,and even can't find the limitations of the optimal solution.The basic genetic algorithm was also often due to the limitation of the algorithm itself,easy early in the process of searching optimal solution,and local search ability is weak,the late slow convergence.Due to these defects,this paper using the hierarchical genetic algorithm being put forward to solve the nonlinear programming problem,and through numerical experiments,the results show that based on hierarchical genetic algorithm for solving a class of nonlinear programming problems is more effective.