改进的无约束多目标优化记忆梯度法  

A Modified Memory Gradient Method for Unconstrainted Multiobjective Optimization

作　　者：李文婷[1] 徐尔[1] 

机构地区：[1]北京科技大学数理学院,北京100083

出　　处：《西南师范大学学报（自然科学版）》2016年第11期20-24,共5页Journal of Southwest China Normal University(Natural Science Edition)

摘　　要：基于无约束单目标记忆梯度法,提出了一种改进的无约束多目标优化问题的记忆梯度法,采用Amijo非精确线搜索产生步长,并证明了算法的收敛性.数值试验表明该算法是有效的.Based on the memory gradient methods fo r unconstrained optimization problems, we present a modified memory gradient method fo r multi-objective optimization w ith o u t constraints, and prove its global convergence which is used Armijo inexact linear research to define step-size at each iterat ion. Numerical re-sults also show that the proposed method is efficient.

关 键 词：记忆梯度法 无约束多目标优化 Amijo线性搜索 Pareto-临界点 

分 类 号：O221[理学—运筹学与控制论]