[1]李荣.多重群体遗传算法在装箱问题中的应用研究[J].计算机技术与发展,2007,(09):247-249.
　LI Rong.Application Study of Multi - Group Genetic Algorithms in Bin- Packing Problem[J].,2007,(09):247-249.
点击复制

多重群体遗传算法在装箱问题中的应用研究()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2007年09期
页码:
247-249
栏目:
应用开发研究
出版日期:
1900-01-01

文章信息/Info

Title:
Application Study of Multi - Group Genetic Algorithms in Bin- Packing Problem
文章编号:
1673-629X（2007）09-0247-03
作者:
李荣
忻州师范学院计算机系
Author(s):
LI Rong
Computer Department of Xinzhou Teacher＇s University
关键词:
多重群体遗传算法; 装箱问题; NP-完备; 种群
Keywords:
multi - group genetic algorithm;  bin - packing;  NP - completeness;  population
分类号:
TP301 O221.7
文献标志码:
A
摘要:
装箱问题是一个有很强应用背景的组合优化问题，求解极为困难。为有效解决该问题，提出了多重群体遗传算法，给出了具体的遗传算法步骤。在算法中采用新陈代谢的选择策略，以更好地保持进化过程中的遗传多样性。实践表明，引人多重群体遗传算法后，装箱效率有明显的改善和提高
Abstract:
Bin- packing problem is a combinatorial optimization problem having very strong application background and its solution is extremely difficult. In order to solve bin - packing problem efficiently, multi - group genetic algorithm is proposed and the complete algorithm procedures are described. In the algorithm, the selection strategy of metabolism which chooses the individual from multiple genera- tion is used so as to keep the variation of the individual in the process of the evolution. The result of simulation indicates that the efficiency of the packing has improved greatly after using the method of multi- group genetic algorithms

相似文献/References:

[1]陈小文 杨静 杨观赐.钢坯入库路径优化模型与算法[J].计算机技术与发展,2009,(12):196.
　CHEN Xiao-wen,YANG Jing,YANG Guan-ci.Models and Algorithms of Path Optimization for Loading of Steel[J].,2009,(09):196.
[2]殷小龙,李君,万明祥. 云环境下基于改进NSGA II的虚拟机调度算法[J].计算机技术与发展,2014,24(08):71.
　YIN Xiao-long,LI Jun,WAN Ming-xiang. Virtual Machines Scheduling Algorithm Based on Improved NSGA II in Cloud Environment[J].,2014,24(09):71.
[3]何利文,唐澄澄,周 睿,等.基于遗传算法的 SDN 增强路径装箱问题研究[J].计算机技术与发展,2019,29(07):150.[doi:10. 3969 / j. issn. 1673-629X. 2019. 07. 030]
　HE Li-wen,TANG Cheng-cheng,ZHOU Rui,et al.Research on Packing Problem of SDN Path Enhancement Based on Genetic Algorithm[J].,2019,29(09):150.[doi:10. 3969 / j. issn. 1673-629X. 2019. 07. 030]

备注/Memo

备注/Memo:
李荣（1974-），女，山西原平人，讲师，硕士，研究方向为中文信息处理、人工智能
更新日期/Last Update: 1900-01-01