HUAI Libo,CUI Rongyi,ZHAO Yahui.Study of classroom management optimal problem based on improved ant colony algorithm[J].Journal of Yanbian University,2014,40(04):335-339.
基于改进的蚁群算法的教室管理优化问题
- Title:
- Study of classroom management optimal problem based on improved ant colony algorithm
- 分类号:
- TP301.6
- 文献标志码:
- A
- 摘要:
- 给出了教室管理问题的一种改进的蚁群优化方法.考虑教室容量、课间距离和单双周课程等因素,对抽象出的数据按优化方向排序,将教室管理问题简化为带权二部图的完备匹配问题; 然后运用基于超立方框架的最大最小蚁群算法进行求解.为有效减少搜索空间,该算法按照教室类型对二部图结点进行分块搜索.实验表明,与基本蚁群算法相比,该算法在解决教室管理优化问题上能得到较优解.
- Abstract:
- An improved ant colony algorithm was presented in order to solve the classroom management problem. This paper sorted the abstracted data along the optimized direction and turned the classroom management problem into the complete matching problem of weighted bipartite graph by analyzing the classroom capacity, the distant between classrooms, single and double week courses etc. Then, we gave optimization method using the improved Max-Min ant colony algorithm based on hyper-cube framework, which searched the node partitioned according to classroom type in order to reducing the searching space. Experimental results show that the improved ant system is able to construct significantly better solutions compared with ACA.
参考文献/References:
[1] 侯文静,马永杰,张燕,等.求解TSP的改进蚁群算法[J].计算机应用研究,2010,27(6):2087-2089.
[2] 崔旭,崔荣一,金小峰,等.基于时间资源的大学排课问题研究[J].延边大学学报:自然科学版,2006,32(4):256-258.
[3] 詹亚坤.基于模拟退火算法的高校排课系统研究[D].东北师范大学,2012.
[4] 王凤,林杰.高校排课问题的图论模型及算法[J].计算机工程与应用,2009,45(27):240-242.
[5] 景雪琴,朱玉芳,杜栋,等.从排课表到教室调度表的设计与实现[J].计算机应用与软件,2004,21(2):123-125.
[6] 余斌,谢昕.基于减小教室流动性的排课算法研究[J].计算机时代,2004(2):22-24.
[7] 倪庆剑,邢汉承,张志政.蚁群算法及其应用研究进展[J].计算机应用与软件,2008,25(8):12-15.
[8] 池元成,蔡国飙.基于蚁群算法的多目标优化[J].计算机工程,2009,35(15):168-169.
[9] Thomas Stützle, Holger H Hoos. MAX-MIN ant system[J]. Future Generation Computer Systems, 2000,16(8):889-914.
[10] 何小虎.优化蚁群算法在排课中的应用策略[J].计算机与数字工程,2012,40(7):33-35.
[11] Broderick Crawford, Ricardo Soto. A Max-Min ant system algorithm to solve the software project scheduling problem[J]. Expert Systems with Applications, 2014(41):6634-6645.
[12] 吴小娟,吕强.新蚁群算法模型在大学课程时间表问题中的应用[J].计算机应用与软件,2009,26(6):80-83.
[13] Christian Blum. The Hyper-Cube framework for ant colony optimization[J]. IEEE Transactions on Systems Man, and Cybernetics Cybernetics-part B: Cybernetics, 2004,34(2):1161-1171.
[14] Li Zhiyong, Wang Yong, Dai Yun, et al. The cloud-based framework for ant colony optimization[C]//Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation. Shanghai, 2009:279-286.
备注/Memo
收稿日期: 2014-07-15 基金项目: 延边大学科技发展计划项目(延大科合字(2013)第12号)作者简介: 怀丽波(1973—),女,副教授,研究方向为优化理论与方法.