Variable Metric Method for Unconstrained Multiobjective Optimization Problems
Variable Metric Method for Unconstrained Multiobjective Optimization Problems
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DOI：
10.1007/s40305-022-00447-z
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发表时间：
2022-07
影响因子：
1.4
通讯作者：
Jian Chen;Gaoxi Li;Xinmin Yang
中科院分区：
文献类型：
--
作者：
Jian Chen;Gaoxi Li;Xinmin Yang
In this paper, we propose a variable metric method for unconstrained multiobjective optimization problems (MOPs). First, a sequence of points is generated using different positive definite matrices in the generic framework. It is proved that accumulation points of the sequence are Pareto critical points. Then, without convexity assumption, strong convergence is established for the proposed method. Moreover, we use a common matrix to approximate the Hessian matrices of all objective functions, along which a new nonmonotone line search technique is proposed to achieve a local superlinear convergence rate. Finally, several numerical results demonstrate the effectiveness of the proposed method.
