A DC Programming Approach to Fractional Problems

被引：0
|
作者：
Gruzdeva, Tatiana [1 ]
Strekalovsky, Alexander [1 ]
机构：
[1] SB RAS, Matrosov Inst Syst Dynam & Control Theory, Lermontov Str 134, Irkutsk 664033, Russia
来源：
LEARNING AND INTELLIGENT OPTIMIZATION (LION 11 2017) | 2017年 / 10556卷
基金：
俄罗斯科学基金会;
关键词：
Fractional optimization; Nonconvex problem; Difference of two convex functions; Equation with vector parameter; Global search algorithm; SUM;
D O I：
10.1007/978-3-319-69404-7_27
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper addresses a rather general fractional optimization problem. There are two ways to reduce the original problem. The first one is a solution of an equation with the optimal value of an auxiliary d.c. optimization problem with a vector parameter. The second one is to solve the second auxiliary problem with nonlinear inequality constraints. Both auxiliary problems turn out to be d.c. optimization problems, which allows to apply Global Optimization Theory [1 1 ,12] and develop two corresponding global search algorithms that have been tested on a number of test problems from the recent publications.
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页码：331 / 337
页数：7
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