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基于多基因分量编码遗传算法的矩形物体布局问题
引用本文:徐生菊,王命延.基于多基因分量编码遗传算法的矩形物体布局问题[J].南昌大学学报(理科版),2007,31(4):399-403.
作者姓名:徐生菊  王命延
作者单位:1. 南昌大学,信息工程学院,江西,南昌,330031;青海大学,财经学院,青海,西宁,810001
2. 南昌大学,信息工程学院,江西,南昌,330031
摘    要:布局问题普遍存在于社会各领域和行业,属于较难解决的NPC问题,传统方法很难找到最优解.遗传算法是一种借鉴生物进化机制和优胜劣汰法则的现代智能算法,具有一定的优势.将基于多基因分量编码的遗传算法应用于矩形物体布局问题的求解,并通过构建遗传算子选择规则库提高遗传算法的自适应性,具有一定的经济意义和理论意义.

关 键 词:遗传算法  动态罚函数  规则  自适应性  多基因  分量编码  遗传算法  矩形  物体  布局问题  Genetic  Algorithm  Coding  Segment  Based  Problem  理论  意义  经济  适应性  规则库  选择  遗传算子  求解  应用
文章编号:1006-0464(2007)04-0399-05
修稿时间:2006-12-10

Rectangles Layout Problem Based on Multi-gene Segment Coding Genetic Algorithm
XU Sheng-ju,WANG Ming-yan.Rectangles Layout Problem Based on Multi-gene Segment Coding Genetic Algorithm[J].Journal of Nanchang University(Natural Science),2007,31(4):399-403.
Authors:XU Sheng-ju  WANG Ming-yan
Institution:1. College of Information Engineering, Nanchang University, Nanchang 330031, China; 2. College of Finance and Economics, Qinghai University, Xining 810001, China
Abstract:Layout problem can be widely found in most social fields and industries. It belongs to NPC problem, which is hard to find out the best solution by using traditional approaches. Genetic algorithm is a kind of modern intelligent algorithm which carries out global random search based on biological evolution mechanism and the rule of the survival of the fittest, so it has some advantages. The paper applies the genetic algorithm based on multi - gene segment coding approaches to solving dimensional rectangles optimal layout problem, and tries to improve self- adaptability of genetic algorithm by building the selection rule - base of genetic operators. It has some economic and academic meaning.
Keywords:genetic algorithm  dynamic penalty function  rules  self - adaptability
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