摘要
本文研究在工程、管理等领域应用广泛的极小极大线性分式规划问题(MLFP).为求解MLFP问题,提出一个新的分支定界算法.在算法中,首先给出一个新的线性松弛化技巧;然后,构造了一个新的分支定界算法.算法的收敛性得以证明.数值实验结果表明了算法的可行性与有效性.
This paper considers minimax linear fractional programming(MLFP)problem,which has many applications in engineering,management,and so on.For solving problem MLFP,a new branch and bound algorithm is proposed.In this algorithm,a new linear relaxation technique is presentedˉrstly,and then,the branch and bound algorithm is developed.The convergence of this algorithm is proved,and some experiments are provided to show its feasibility and e±ciency.
作者
汪春峰
蒋妍
申培萍
WANG Chunfeng;JIANG Yan;SHEN Peiping(College of Mathematics and Information, Henan Normal University, Xinxiang 453007, China;Foundation Department, Zhengzhou Tourism College, Zhengzhou 450009, China)
出处
《数学杂志》
2018年第1期113-123,共11页
Journal of Mathematics
基金
Supported by NSFC(U1404105)
the Key Scientific and Technological Project of Henan Province(142102210058)
the Youth Science Foundation of Henan Normal University(2013qk02)
Henan Normal University National Research Project to Cultivate the Funded Projects(01016400105)
the Henan Normal University Youth Backbone Teacher Training
关键词
线性松弛
全局优化
极小极大线性分式规划
分支定界
linear relaxation
global optimization
minimax linear fractional programming
branch and bound
