Parameter estimation in branch and bound algorithms for large-scale discrete optimization problems

被引：0
|
作者：
Sigal, IK [1 ]
机构：
[1] Russian Acad Sci, Ctr Comp, Moscow 119991, Russia
来源：
JOURNAL OF COMPUTER AND SYSTEMS SCIENCES INTERNATIONAL | 2005年 / 44卷 / 04期
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The parameters of branch and bound algorithms for some discrete optimization problems of large dimensions are studied, when precise and approximate solutions are sought. For both these cases, a general scheme of parameterization of algorithms is proposed. Some new parameters characterizing the solution process are introduced, and the ranges of previously used parameters are specified in relation to the computational resources.
引用
收藏
页码：594 / 599
页数：6
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