求解一类多目标优化问题的极大熵差分进化算法  

Differential evolution algorithm for solving multiobjective optimization problem based on maximum entropy function methods

作　　者：雍龙泉[1] 

机构地区：[1]陕西理工学院数学与计算机科学学院,陕西汉中723001

出　　处：《中南大学学报（自然科学版）》2013年第S2期160-164,共5页Journal of Central South University:Science and Technology

基　　金：陕西省教育厅科研计划项目(12JK0863)

摘　　要：给出了求解多目标优化问题的1种新算法。首先利用评价函数法,将多目标优化问题转化为1个不可微的单目标优化问题;进而通过极大熵函数,将不可微优化问题转化为1个带有参数的无约束优化问题,然后利用差分进化算法对其进行求解。数值结果表明:该算法只需较少的迭代次数就可以获得原问题较好的近似解。A new method for solving multiobjective optimization problem was proposed.First,multiobjective optimization problem was reformulated as a non-smooth single objective optimization problem via evaluation function,and a smooth single objective optimization problem with parameter via the maximum entropy function,and then using the differential evolution algorithm to solve the converted problem.Numerical results show that the algorithm only requires a few iterations to get a good approximate solution of original problem.

关 键 词：多目标优化 极大熵函数 差分进化算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O221.6[自动化与计算机技术—控制科学与工程]