Journal Home Online First Current Issue Archive For Authors Journal Information 中文版

Strategic Study of CAE >> 2014, Volume 16, Issue 8

Modified Binary Artificial Bee Colony Algorithm forMultidimensional Knapsack Problem

School of Mathematics,Nanjing Normal University Taizhou College,Taizhou,Jiangsu 225300,China

Funding project:南京师范大学泰州学院资助项目(Q201232) Received: 2013-11-11 Available online: 2014-08-13 13:46:16.000

Next Previous

Abstract

The binary artificial bee colony algorithm has the shortcomings of slower convergence speed and falling into local optimum easily. According to the defects, a modified binary artificial bee colony algorithm is proposed. The algorithm redesign neighborhood search formula in artificial bee colony algorithm, the probability of the food position depends on the Bayes formula. The modified algorithm was used for solving multidimensional knapsack problem, during the evolution process, it uses the greedy algorithm repairs the infeasible solution and rectify knapsack resources with insufficient use. The simulation results show the feasibility and effectiveness of the proposed algorithm.

References

[ 1 ] Karaboga D. An idea based on honey bee swarm for numerical optimization [R]. Technical Report-TR06,Kayseri:Erciyes University,Engineering Faculty,Computer Engineering Department,2005. link1

[ 2 ] Karaboga D,Basturk B. A powerful and efficient algorithm for numerical function optimization:artificial bee colony (ABC) algorithm [J]. Journal of Global Optimization,2007,39(3):459- 471. link1

[ 3 ] Karaboga D,Basturk B. Artificial bee colony (ABC) optimization algorithm for solving constrained optimization [J]. Foundations of Fuzzy Logic and Soft Computing,2007,4529:789-798. link1

[ 4 ] Karaboga D,Basturk B. On the performance of artificial bee colony (ABC) algorithm [J]. Applied Soft Computing,2008,8(1): 687-697. link1

[ 5 ] Karaboga D. A new design method based on artificial bee colony algorithm for digital IIR filters [J]. Journal of the Franklin Institute,2009,346(4):328-348. link1

[ 6 ] Singh A. An artificial bee colony algorithm for the leaf- constrained minimum spanning tree problem [J]. Applied Soft Computing,2009,9(2):625-631. link1

[ 7 ] 胡中华,赵 敏. 基于人工蜂群算法的机器人路径规划[J]. 电 焊机,2009,39(4):93-96. link1

[ 8 ] 胡中华,赵 敏. 基于人工蜂群算法的TSP仿真[J]. 北京理工 大学学报,2009,29(11):978-982. link1

[ 9 ] 孙晓雅,林 焰. 改进的人工蜂群算法求解任务指派问题[J]. 微电子学与计算机,2012,29(1):23-26. link1

[10] Marinakis Y,Marinaki M,Matsatsinis N. A hybrid discrete artificial bee colony-GRASP algorithm for clustering [C]//International Conference on Computers Industrial Engineering. Troyes,France:[s.n.],2009:548-553. link1

[11] Pampará G,Engelbrecht A P. Binary artificial bee colony optimization [C]//IEEE Symposium on Swarm Intelligence. Paris: IEEE,2011:1-8. link1

[12] Kennedy J,Eberhart R C. A discrete binary version of the particle swarm algorithm [C]//Proceedings of IEEE Conference on Systems,Man,and Cybernetics. Orlando,1997,5:4104- 4108. link1

[13] Pampará G,Engelbrecht A P,Franken N. Binary differential evolution [C]//IEEE Congress on Evolutionary Computation. Vancouver:IEEE,2006:1873-1879.

[14] 贺 一,邱玉辉,刘光远,等.多维背包问题的禁忌搜索求 解[J]. 计算机科学,2006,33( 9) :169-172. link1

[15] 喻学才,张田文. 多维背包问题的一个蚁群优化算法[J]. 计算 机学报,2008,31(5):810-819. link1

[16] 孔 民,田 澎,李相勇. 多维背包问题的二进制蚂蚁算 法[J]. 管理科学学报,2009,12(2):44-53. link1

[17] 冀俊忠,黄 振,刘椿年. 基于变异和信息素扩散的多维背包 问题的蚁群算法[J]. 计算机研究与发展,2009,46(4):644- 654. link1

[18] 刘 勇,马 良. 元胞微粒群算法及其在多维背包问题中的 应用[J]. 管理科学学报,2011,14(1):86-96. link1

[19] 杜 巍,李树茁,陈煜聪. 一种求解多维背包问题的小世界算 法[J]. 西安交通大学学报,2009,43(2):10-14. link1

[20] 刘 毅,宋玉阶. 多维背包问题的 DNA 计算[J]. 生物数学学 报,2008,23(1):180-186. link1

[21] 李春梅,马 良. 求解多维 0-1 背包问题的人工鱼群算法[J]. 数学的实践与认识,2010,40(17):195-199. link1

Related Research