基于演化计算的线性规划原对偶内点法中的初始点选取算法

Initial Point Selection in Primal-Dual Interior Point Method for Linear Programming Based on Evolutionary Algorithm

采用原对偶内点法求解线性规划问题,对初始点要求严格。根据初始可行内点的准则,定义了相应的达成度函数,并由达成度函数定义了适应值函数,从而提出了基于演化计算的线性规划原对偶内点法中的初始点选取算法。该算法基于和声搜索演化算法实现,经数值实验测试,结果表明,对所选取测试的典型线性规划问题,算法都能求得大部分问题的初始可行内点。

The primal-dual interior point method requires strict initial feasible points in solving linear programming problems. The degree function is given based on the criterion of the initial feasible point in the primal-dual interior point method,and the fitness function in the evolutionary algorithm is designated by the degree function. The initial feasible point selection of the primal-dual interior point method for linear programming based on the evolutionary computation is proposed. It is taken by the harmony search.Numerical experiments show that the algorithm can find an initial feasible point of most given problems,thus validating the effectiveness of the algorithm.