） 摘要： 针对一类0-1背包问题提出一种新的混合遗传算法
充分发挥变异操作在遗传算法中重要而基本的作用
贪婪遗传算法使用贪婪法则产生第一个染色体
并在进化过程中利用贪婪算子改进部分可行解
） Abstract： A new HGA for a class of 0-1KP called Greedy Genetic Algorithm is presented
GGA turns greedy principle to advantage
The greedy approach is used for generating the first chromosome, and made use of the greedy-operator to improve some feasible solutions further in the course of evolution
GGA uses larger mutation probability and smaller crossover probability at the same time to overcome GA’s limitation, mutation operation in GA plays an important and fundamental role in
Numerous computational experiments have been carried out on about 400,000 well-structured new classes of instances, and a comparative analysis with some recent state-of-art exact algorithms for the 0-1KP is given
It is found that the average computing time of GGA grow to be less than the time of the exact algorithms in company with an increase in coefficients
The average computing time to search for an optimal solution is between 0
3ms and 430
6ms, and the average generation is 1 to 40
Keywords： 0-1 knapsack problem;greedy algorithm;genetic algorithms;greedy genetic algorithm 下载PDF阅读器 PDF全文下载： 初稿 （ 196 ） 作者简介： 通信联系人： 【收录情况】 中国科技论文在线： 金怀群
一类0-1背包问题的贪婪遗传算法[EB/OL]
北京：中国科技论文在线
平均在0
3ms与430
6ms之间
而平均代数为1到40
贪婪遗传算法 Jin Huaiqun * （ Department of Mathematics and Information Technology, Hanshan Normal University
【详情见下载】
