A BRANCH AND BOUND ALGORITHM FOR SOLVING THE SUM OF GENERALIZED POLYNOMIAL FRACTIONAL PROGRAMMING PROBLEM

被引：0
|
作者：
Liu, Xia [1 ]
Ma, Xiao-Hua [1 ]
Jing, Xia [1 ]
机构：
[1] North Minzu Univ, Ningxia Collaborat Innovat Ctr Sci Comp & Intellig, Yinchuan 750021, Peoples R China
来源：
JOURNAL OF NONLINEAR AND CONVEX ANALYSIS | 2024年 / 25卷 / 03期
关键词：
Generalized polynomial fractional programming; global optimization; branch and bound; linearized relaxation; GLOBAL OPTIMIZATION ALGORITHM; RATIOS;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper aims at the generalized polynomial fractional programming problem (GPFP)'s global optimal solution. By utilizing the exponential convex -concave envelopes to relax the original problem into linear fractional programming problem (LRP1), then adding auxiliary variables for each linear fraction and exploiting the bilinear convex -concave envelopes to construct a linear programming relaxation (LRP). Then the algorithm (YBBA) is proposed and proved to be convergent. Finally, the algorithms effectiveness is verified by numerical experiments.
引用
收藏
页码：601 / 613
页数：13
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