摘要
本文对一类非凸规划问题(NP)给出一确定性全局优化算法.这类问题包括:在非凸的可行域上极小化有限个带指数的线性函数乘积的和与差,广义线性多乘积规划,多项式规划等.通过利用等价问题和线性化技巧提出的算法收敛到问题(NP)的全局极小.
This paper presents a deterministic global optimization algorithm for solving a class of nonconvex programming problems （NP）. This class includes such problems as：minimizing a sum,or difference for product or division of a finite number of linear functions with exponents,generalized linear multiplicative programming, polynomial programming,etc.-over nonconvex feasible region. By utilizing equivalent problem and linear relaxation technique,the proposed algorithm is convergent to the global minimum of （NP）.
出处
《应用数学》
CSCD
北大核心
2008年第2期270-276,共7页
Mathematica Applicata
基金
the National Natural Science Foundation of China(10671057)
the Natu-ral Science Foundation of Henan Institute of Science and Technology(06054)
关键词
非凸规划
全局优化
线性松弛
分枝定界
Nonconvex programming
Global optimization
Linear relaxation
Branch and bound
