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[1]钟 静,应 宏.优化和约束推理的动态分布式双向导遗传算法[J].重庆师范大学学报(自然科学版),2009,26(02):94-98.[doi:10.11721/cqnuj20090221]
　ZHONG Jing,YING Hong.A Dynamic Distributed Double Guided Genetic Algorithm for Optimization and Constraint Reasoning[J].期刊社,2009,26(02):94-98.[doi:10.11721/cqnuj20090221]
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优化和约束推理的动态分布式双向导遗传算法

重庆师范大学学报（自然科学版）[ISSN:1672-6693/CN:50-1165/N] 卷: 26 期数: 2009年02期 页码: 94-98 栏目: 理论与应用研究 出版日期: 2009-04-25
Title:
A Dynamic Distributed Double Guided Genetic Algorithm for Optimization and Constraint Reasoning
作者:
钟 静; 应 宏
重庆三峡学院 数学与计算机科学学院，重庆 万州 404000
Author(s):
ZHONG Jing; YING Hong
College of Mathematics and Computer Science, Chongqing Three Gorges University, Chongqing 404000 ， China
关键词:
FONT-FAMILY: 宋体;  LINE-HEIGHT: 125%">优化; 约束推理; 动态分布式 FONT-FAMILY: ’Times New Roman’;  LINE-HEIGHT: 125%">;  FONT-FAMILY: 宋体;  LINE-HEIGHT: 125%">双向导; 遗传算法
Keywords:
FONT-FAMILY: ’Times New Roman’;  LINE-HEIGHT: 125%">optimization;  constraint reasoning;  dynamic distributed;  double duided;  genetic algorithm
DOI:
10.11721/cqnuj20090221
文献标志码:
A
摘要:
为了解决优化和约束推理，基于向导遗传算法（GGA）和分布式向导遗传算法（DGGA），通过引入向导概率Pguid、本地优化监测LOD和权ε共3个新参数，提出了一种D 3G 2A算法的改进算法。该算法采用多代理方法，不仅使搜索过程多样化，避免出现局部最优，而且代理能计算各自的遗传参数。将改进的D 3 G 2 A 和GGA用于随机生成的二元CSPs，实验表明，D 3 G 2 A能有效改善适应度值和节省CPU时间开销，算法的性能得到提高。
Abstract:
D3G2A is a new multi-agent approach which addresses additive constraint satisfaction problem. This approach is inspired by the guided genetic algorithm （ GGA ） and by the dynamic distributed double guided genetic algorithm for Max_CSPs. It consists of agents dynamically created and cooperating in order to solve problem with each agent performs its own GA. First, our approach is enhanced by three parameters ， guidance probability ， local optima detector ， weight, which allow not only diversification but also escaping from local optima. Second, the GGAs performed agents will no longer be the same. In fact our approach will let the agents able to count their own GA parameters. In order to show D3G2A advantages, the approach and the GGA are applied on the randomly generated binary constraints satisfaction problems. And the result shows that D3G2A is efficient in better fitness values and shorter CPU time

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更新日期/Last Update: 2009-06-03