求解多目标规划问题的一种新的群体搜索算法

针对带有边界变量的多目标优化问题，提出一个新的随机群体搜索算法，该方法在可行域内随机选取N个样本点，把每个样本点看成带电粒子。根据不同目标函数，分别定义其电荷，针对每个样本点根据不同目标函数按照电磁学原理计算出合力，然后把各个合力线性加权作为该点搜索方向，以便求得新的群体．最后，把给出的算法应用到两个实例中。并与遗传算法、蚁群算法进行比较，数值结果表明算法是可行的和有效的．

A new random group search algorithm for solving the multi-objective programming problems

A new random group search algorithm is proposed for solving the multi-objective programming problems with box constraints. In this algorithm, N sample points are randomly selected in the feasible region, each sample points is regarded as the charged particle, according to the different objective function to define its charge. Based on the principle of electromagnetism, we calculate total force for each sample point under different objective function. Then, all of the point total forces are linearly weighted as the point search direction to seek new sample points. Finally, the algorithm is applied to two examples, and compare to GA and SA. The numerical results show that the algorithm is feasible and effective.