THE POWER OF NATURAL EVOLUTION IN SOLVING DISTRIBUTED CONSTRAINT OPTIMIZATION PROBLEMS

被引：0
|
作者：
Yang Xiaolei [1 ]
Feng Youqian [1 ]
Yuan Xiujiu [1 ]
Zhao Xuejun [1 ]
机构：
[1] Air Force Engn Univ, Sch Air & Missile Def, Xian 710051, Peoples R China
来源：
JOURNAL OF THE BALKAN TRIBOLOGICAL ASSOCIATION | 2016年 / 22卷 / 03期
基金：
中国国家自然科学基金;
关键词：
distributed constraint optimization; genetic algorithm; incomplete;
D O I：
暂无
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
As a popular search method, genetic algorithm (GA) has been applied to a wide range of optimization problems. This paper proposes GA-DCOP, a novel incomplete distributed algorithm which exploits GA's powerful global search ability to solve distributed constraint optimization problems. Concretely, within the DCOP framework, each agent is given the authority to conduct genetic operations independently. The proposed algorithm is evaluated experimentally and compared to other DCOP algorithms. The experimental results demonstrate that GA-DCOP outperforms several state-of-the-art algorithms in either solution quality or in simulated time.
引用
收藏
页码：2476 / 2483
页数：8
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