摘要
重点研究了解决多设施韦伯问题(MFWP)的有效算法。首先,将MFWP重新表述为它的等价形式,然后提出一种半光滑牛顿增广拉格朗日(Ssnal)算法来求解MFWP,并且刻画了Ssnal算法的全局收敛性和局部渐近超线性收敛性。最后,在数据集上进行数值实验,结果表明,Ssnal算法在鲁棒性和计算效率方面都优于双曲近似过程(HAP)算法和交替方向乘子法(ADMM)。
An effective algorithm for solving the multi-facility Weber problem(MFWP)is mainly studied.Firstly,MFWP is reformulated as its equivalent form and then a semi-smooth Newtonian augmented Lagrange(Ssnal)algorithm is proposed to solve MFWP.The global convergence and local asymptotic superlinear convergence of the Ssnal algorithm are also described.Finally,the experimental results tested on the dataset show that the Ssnal algorithm is superior to the HAP algorithm and the ADMM in terms of robustness and computational efficiency.
作者
杨子斌
刘勇进
YANG Zibin;LIU Yongjin(School of Mathematics and Statistics,Fuzhou University,Fuzhou Fujian 350108,China)
出处
《莆田学院学报》
2023年第2期18-25,共8页
Journal of putian University
基金
国家自然科学基金面上项目(11871153)。
关键词
多设施韦伯问题
半光滑牛顿算法
增广拉格朗日算法
multi-facility Weber problem
semismooth Newton method
augmented Lagrangian algorithm
