A cellular genetic algorithm for satisfiability problems

被引：0
|
作者：
Pizzuti, C
Spezzano, G
Ursino, D
机构：
来源：
ADVANCES IN INTELLIGENT SYSTEMS | 1997年 / 41卷
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：
This paper presents a new evolutionary method for the satisfiability problem based on a cellular genetic algorithm. In this method a global search on a random initial population of individuals is performed by local selective generation of new strings according to new defined genetic operators, The algorithm adopts a diffusion model of information among chromosomes by realizing a one-dimensional cellular automata in which the neighborhood relation is based on a fixed variable radius. Furthermore, the cellular algorithm is suitable for a direct parallel implementation.
引用
收藏
页码：408 / 413
页数：6
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