An improved genetic algorithm for solving packing problem

被引：0
|
作者：
Li Zhi-yan [1 ]
机构：
[1] Hohai Univ, Dept Math & Phys, Changzhou Campus, Changzhou, Peoples R China
来源：
PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY | 2016年 / 60卷
关键词：
Bin-Packing Problem; Genetic Algorithm; Best Fit Decrease; Combination Optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Targeted at solving slow rate of convergence in the current genetic algorithm, an improved genetic algorithm is put forward in the article. The current genetic algorithm is improved by adding the best fit decrease algorithm to generate individuals into the initial population, conversing the preservation strategy and fitness of the optimum individual. To verify the validness of the algorithm, simulation experiments are designed. And the result of these experiments shows that the improved algorithm has the bigger probability to find the optimal solution and faster solution speed.
引用
收藏
页码：1816 / 1821
页数：6
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