[1]严宏[][]. 教学资源配置优化中遗传算法的应用与改进[J].计算机技术与发展,2016,26(03):130-134.
　YAN Hong[][]. Application and Improvement of Genetic Algorithm for Optimization in Allocating Teaching Resources[J].,2016,26(03):130-134.
点击复制

 教学资源配置优化中遗传算法的应用与改进()
分享到：

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

卷:
26
期数:
2016年03期
页码:
130-134
栏目:
应用开发研究
出版日期:
2016-03-10

文章信息/Info

Title:
 Application and Improvement of Genetic Algorithm for Optimization in Allocating Teaching Resources
文章编号:
1673-629X（2016)03-0130-05
作者:
 严宏[1][2]
1. 中国民用航空飞行学院；2.四川大学 视觉合成图形图像技术国家重点学科实验室
Author(s):
 YAN Hong[1][2]
关键词:
 ; 资源配置; 遗传算法; 十进制编码; 适应度函数; 交叉算子
Keywords:
 ; resources allocation; genetic algorithm; decimal encoding; fitness function; crossover operator
分类号:
TP18
文献标志码:
A
摘要:
 对于临时新增教学任务，教学资源安排不同于学期开始前的教学资源配置，通常具有特定的配置需求。在教学资源有限的情况下，为了使新增教学班级配置的教室更加一致或接近，避免频繁变动教室给教学带来的不便，使用遗传算法进行教室资源的分配，并根据应用需求进行了改进。其中设计了更加适宜的十进制编码，提出的适应度函数能有效地对教室资源的一致或接近程度进行量化计算。根据染色体编码特点和优化目标，对遗传算子进行选择和改进，特别对单点交叉进行改进尽可能地提高交叉后的适应度，同时保持种群的多样性。实验结果表明，改进的遗传算法相对于标准遗传算法在用时更少的情况下得到的教学资源分配更加满足优化目标，计算效率得以提高，并且成功应用于实际的教学资源配置。
Abstract:
 For temporarily added curriculum,the arrangement of teaching resources which usually has some specific requirements is differ-ent from that done before a semester begins. In the case of limited teaching resources,an improved genetic algorithm was proposed for op-timizing the consistency and nearness of the classrooms allocated for temporary curriculum,with aim to avoid the inconvenience to teach-ing caused by frequent change of classrooms. Based on the requirement of the given application in this paper,a more efficient decimal en-coding was developed. Correspondingly,a suitable fitness function was proposed to quantitatively calculate the consistency and nearness of the allocated classrooms. According to the characteristic of the chromosome encoding and the optimization goal,the algorithm selected ex-isting genetic operators and improved them,especially the modified one-point crossover that attempts to enhance the fitness value and maintain the diversity of population. The experimental results show that the improved genetic algorithm,which has been successfully ap-plied,can achieve more optimal solution within a shorter period of time when compared with the standard genetic algorithm.

相似文献/References:

[1]黄妮 吴晓军.基于时间约束的软件工程资源配置Petri网检测模型[J].计算机技术与发展,2012,(04):21.
　HUANG Ni,WU xiao-jun.Petri Net Detecting Model of Software Engineering Resource Configuration Based on Time Constraint[J].,2012,(03):21.
[2]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(03):1.
[3]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(03):5.
[4]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(03):13.
[5]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(03):21.
[6]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(03):25.
[7]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(03):29.
[8]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(03):34.
[9]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
　SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(03):38.
[10]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
　YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(03):43.

更新日期/Last Update: 2016-06-14