丁海軍、馮慶嫻(2009)。基於boltzmann選擇策略的人工蜂群演算法。計算機工程與應用,45(31),53。
尹邦嚴、王敬育(2004)。使用螞蟻族群最佳化求解資源分配問題。科技與管理學術研討會,台灣科技大學。
岑海堂、陳五一(2007)。仿生學概念及其演變。機械設計,24(7),64-66。
李曉磊、路飛、田國會、錢積新(2004)。組合優化問題的人工魚群算法應用。山東大學學報,34(5),64-67
肖永豪、余衛孙(2010)。基於蜂群算法的圖像邊緣檢測。計算機應用研究,27(7),2748-2750。
周祖德、劉東(2009)。基於多代理和蜂群算法的車間調度系統研究。武漢理工大學學報,31(1),82-86。
林豐澤(2005)。演化式計算下篇:基因演算法以及三種應用實例。智慧科技與應用統計學報,3(1),29-56。邱顯明、謝國倫、蘇先知(2004)。基因演算法應用於捷運轉乘公車路網設計之研究。中國土木水利工程學刊,16(4),635-649。胡中華、趙敏(2009)。基於人工蜂群算法的機器人路徑規劃。電焊機,39(4),93-96。
胡珂、李迅波、王振林(2011)。改進的人工蜂群算法性能。計算機應用,31(4),1107-1110。
苗金鳳、王洪國、邵增珍、趙學臣(2010)。基於多級搜索區域的協同進化遺傳算法。計算機應用研究,27(9),3345-3351。
張青、康立山、李大農(2008)。群智能算法及其應用。黃網師範學院學報,28(6),44-48。
郭定(2009,A)。基因演算法中不同選擇策略的替代性與互補性。科學與工程技術期刊,5(2),25-34。葉進儀、林彣珊、朱慶餘(2007)。應用平行基因演算法改善護理人員排班品質。品質學報,14(3),337-350。趙小強、張守明(2010)。基於人工蜂群的模糊聚類算法。蘭州理工大學學報,36(5),79-82。
暴勵、曾建潮(2010)。自適應搜索空間的混沌蜂群算法。計算機應用研究,27(4),1330-1334。
樊小毛、馬良(2010)。約束平面選址問題的蜂群優化算法。上海理工大學學報, 32(4), 378-380。
鄭富升,”蟑螂演算法在含限制條件問題的應用”,第十屆人工智慧與應用研討會論文集,2005 年。
賴智錦、蔡明冀(2004)。應用粒子群尋優演算法於垃圾郵件屬性之篩選。行政院國家科學委員會專題研究成果報告(報告編號:NSC 93-2213-E-024-008),未出版。
簡璟蔚(2011)。改良突變權重的差分進化演算法。先進工程學刊,6(4),255-261。
羅鈞、樊鵬程(2009)。基於遺傳交叉因子的改進蜂群優化算法。計算機應用研究,26(10),3716-3717。
Aderhold, A., Diwold, K., Scheidler, A., &; Middendorf, M. (2010). Artificial bee colony optimization: A new selection scheme and its performance. Computational Intelligence,284(2),283-294.
Alatas, B. (2010). Chaotic bee colony algorithms for global numerical optimization. Expert Systems with Applications, 37(8), 5682-5687.
Alfi, A., &; Modares, H. (2011). System identification and control using adaptive particle swarm optimization. Applied Mathematical Modelling, 35(3), 1210-1221.
Bonabeau, E. ,Dorigo, M. &; Theraulaz, G.(1999).Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press.
Chen, C. (2011). Two-layer particle swarm optimization for unconstrained optimization problems. Applied Soft Computing, 11(1), 295-304.
Chen, D., &; Zhao, C. (2009). Particle swarm optimization with adaptive population size and its application. Applied Soft Computing, 9(1), 39-48.doi:0.1016/j.asoc.2008.03.001.
Dongli.Z ., Xinping.G.,Yinggan.T.&; Yong.,T(2011, May). Modified Artificial Bee Colony Algorithms for Numerical Optimization. Intelligent Systems and Applications (ISA), Symposium conducted at the meeting of Qinhuangdao, China.
Gao,W.D., Liu,S.Y.(2011). A modified artificial bee colony algorithm. Computers &; Operations Research,39(3),687-697.
Guo,P.,Cheng,W.,&; Liang,J(2011,July). Global artificial bee colony search algorithm for numerical function optimization. Natural Computation (ICNC), Symposium conducted at the meeting of Chengdu, China.
Guoqiang L., Peifeng,N., &;Xingjun,X.(2011). Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Applied Soft Computing,12(1),320-332.
Holland ,H.(1975)。 Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligenc.
Price, K. V., Storn, R., M., &;Lampinen, J. A. ,“Differential Evolution: A Practical Approach to Global Optimization,” Springer-Verlag, Berlin, Germany, 2005.
Kao, Y., &; Zahara, E. (2008). A hybrid genetic algorithm and particle swarm optimization for multimodal functions. Applied Soft Computing, 8(2), 849-857. doi:10.1016/j.asoc.2007.07.002.
Karaboga, D.(2005). An idea based on honey bee searm for numerical optimization. Erciyes University, Kayseri, Turkey, Technical Report-TR06.
Krink, T. ,Filipic, B., &; Fogel, G.B(2004,June). Noisy Optimization Problems - A Particular Challenge for Differential Evolution. Evolutionary Computation,1(1), 332-339.
Dorigo, M., Maniezzo,V., &; Colorni, A., “The Ant System: An Autocatalytic Optimizing Process,” Technical Report No. 91-016 Revised, Politecnico di Milano, Italy, 1991.
Eberhart,R. C.,&;Kennedy,J., “A new optimizer using particle swarm theory,” Proceedings of the sixth international symposium on micro machine and human science, IEEE service center, Piscataway, NJ (Nagoya, Japan), pp. 39-43, 1995.
Shelokar, P. S., Siarry, P., Jayaraman, V. K., &; Kulkarni, B. D. (2007). Particle swarm and ant colony algorithms hybridized for improved continuous optimization. Applied Mathematics and Computation, 188(1), 129-142.doi:10.1016/j.amc.2006.09.098.
Shi, Y.j., Qu, F.z., Chen, W., &; Li, B. (2010). An artificial bee colony with random key for resource-constrained project scheduling.Lecture Notes in Computer Science,6329(2), 148-157.
Toğan, V., &; Daloğlu, A. T. (2008). An improved genetic algorithm with initial population strategy and self-adaptive member grouping. Computers &; Structures, 86(11-12), 1204-1218.doi:10.1016/j.compstruc.2007.11.006.
Xiaohu, S., Yanwen ,L., Haijun, L., Renchu ,G., Liupu ,W., &; Yanchun ,L. (2010,August). An integrated algorithm based on artificial bee colony and particle swarm optimization. In S. Yue (Chair), Natural Computation (ICNC), Symposium conducted at the meeting of Yantai, China.
Zhang, C., Ouyang, D., &; Ning, J. (2010). An artificial bee colony approach for clustering. Expert Systems with Applications, 37(7), 4761-4767.
Zhi, F. H., Guang, H. G., &; Han, H. (2007 ,August). A particle swarm optimization algorithm with differential evolution. In C. S. Ming (Chair),Machine Learning and Cybernetics. Symposium conducted at the meeting of South China University of Technology, Hong Kong.
Zhu, G., &; Kwong, S. (2010). Gbest-guided artificial bee colony algorithm for numerical function optimization. Applied Mathematics and Computation, 217(7), 3166-3173.