Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

被引:13
作者
Chen, Tinggui [1 ]
Xiao, Renbin [2 ]
机构
[1] Zhejiang Gongshang Univ, Coll Comp Sci & Informat Engn, Hangzhou 310018, Zhejiang, Peoples R China
[2] Huazhong Univ Sci & Technol, Inst Syst Engn, Wuhan 430074, Hubei Province, Peoples R China
来源
SCIENTIFIC WORLD JOURNAL | 2014年
基金
高等学校博士学科点专项科研基金; 中国国家自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION;
D O I
10.1155/2014/438260
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.
引用
收藏
页数:12
相关论文
共 32 条
[1]   Chaotic bee colony algorithms for global numerical optimization [J].
Alatas, Bilal .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (08) :5682-5687
[2]   Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm [J].
Alvarado-Iniesta, Alejandro ;
Garcia-Alcaraz, Jorge L. ;
Ivan Rodriguez-Borbon, Manuel ;
Maldonado, Aide .
EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (12) :4785-4790
[3]  
[Anonymous], J BIOINFORMATICS INT
[4]   The best-so-far selection in Artificial Bee Colony algorithm [J].
Banharnsakun, Anan ;
Achalakul, Tiranee ;
Sirinaovakul, Booncharoen .
APPLIED SOFT COMPUTING, 2011, 11 (02) :2888-2901
[5]  
Bateni M, 2012, INT J BIO-INSPIR COM, V4, P181, DOI 10.1504/IJBIC.2012.047240
[6]  
Bonabeau E., 1999, Swarm Intelligence: From Natural to Artificial Systems, V1st
[7]   Assembly planning using a novel immune approach [J].
Cao, P. -B. ;
Xiao, R. -B. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2007, 31 (7-8) :770-782
[8]   A novel artificial bee colony algorithm for solving the supply chain network design under disruption scenarios [J].
Chen, Ting-gui ;
Ju, Chun-hua .
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2013, 47 (2-3) :289-296
[9]   A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization [J].
Chen, Tinggui ;
Xiao, Renbin .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
[10]  
Cui ZH, 2010, J MULT-VALUED LOG S, V16, P585