面向非线性规划问题的混合式遗传算法

HYBRID GENETIC ALGORITHM FOR SOLVING NON LINEAR PROGRAMMING PROBLEM

面向非线性规划问题 ,通过引入准可行方向、准可行方向的可行度等新概念 ,提出了描述和度量非可行点 (染色体 )的新方法 ;通过嵌入非可行染色体的信息于评价函数中 ,突破传统的给非可行染色体以大的惩罚的思想 ,提出了三种新的评价非可行染色体的方法 .基于梯度方向搜索和新的评价方法 ,提出了一种新的沿权重梯度方向变异的混合式遗传算法( HGA) .

Based on the introduction of the new concepts of semi feasible direction,feasible degree of semi feasible direction,feasible degree of illegal points ‘belonging to' feasible domain,etc.this paper proposes a new method for formulating and evaluating illegal points and three new kinds of evaluation functions,and develops a special hybrid genetic algorithm(HGA) with penalty function and weighted gradient direction search for non linear programming problems.Simulation shows that this method is effective.