A Conjugate Directions-Type Procedure for Quadratic Multiobjective Optimization
A Conjugate Directions-Type Procedure for Quadratic Multiobjective Optimization
复制标题
二次多目标优化的共轭方向型程序
DOI：
10.1080/02331934.2021.1914034
复制
发表时间：
2021
期刊：
影响因子：
2.2
通讯作者：
Ariane Masuda
中科院分区：
文献类型：
--
作者：
Ellen Hidemi Fukuda;Luis M. Grana Drummond;Ariane Masuda
提出了求解无约束二次多目标问题的实值共轭方向法的推广方法。正如在单值对应中一样，该过程需要一组关于所有二次目标分量的正定矩阵同时共轭的方向。同样，多准则版本在每次迭代时通过单变量强凸函数的无约束最小化来计算步长。当采用弱增(强增)辅助函数时，该方案在有限次迭代中产生弱Pareto(Pareto)最优解。
We propose an extension of the real-valued conjugate directions method for unconstrained quadratic multiobjective problems. As in the single-valued counterpart, the procedure requires a set of directions that are simultaneously conjugate with respect to the positive definite matrices of all quadratic objective components. Likewise, the multicriteria version computes the steplength by means of the unconstrained minimization of a single-variable strongly convex function at each iteration. When it is implemented with a weakly-increasing (strongly-increasing) auxiliary function, the scheme produces weak Pareto (Pareto) optima in finitely many iterations.