Artificial Bee Colony (ABC) Algorithm for Constrained Optimization Improved with Genetic Operators

被引：73

作者：

Bacanin, Nebojsa ^{[1
]}

Tuba, Milan ^{[1
]}

机构：

[1] Megatrend Univ Belgrade, Fac Comp Sci, N Belgrade 11070, Serbia

来源：

STUDIES IN INFORMATICS AND CONTROL | 2012年 / 21卷 / 02期

关键词：

Artificial bee colony (ABC); Constrained optimization; Swarm intelligence; Nature inspired metaheuristics; STRATEGY;

D O I：

10.24846/v21i2y201203

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to unconstrained optimization problems and later it was adjusted for constrained problems as well. In this paper we introduce modifications to the ABC algorithm for constrained optimization problems that improve performance of the algorithm. Modifications are based on genetic algorithm (GA) operators and are applied to the creation of new candidate solutions. We implemented our modified algorithm and tested it on 13 standard benchmark functions. The results were compared to the results of the latest (2011) Karaboga and Akay's ABC algorithm and other state-of-the-art algorithms where our modified algorithm showed improved performance considering best solutions and even more considering mean solutions.

引用

页码：137 / 146

页数：10

共 50 条

[41] Improved and Effective Artificial Bee Colony Clustering Algorithm for Social Media Data (I-ABC) [J].

Shrivastava, Akash ;

Garg, M. L. .

JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES, 2019, 14 (01) :289-304

[42] An Efficient Artificial Bee Colony Algorithm With an Improved Linkage Identification Method [J].

Gao, Hao ;

Fu, Zheng ;

Pun, Chi-Man ;

Zhang, Jun ;

Kwong, Sam .

IEEE TRANSACTIONS ON CYBERNETICS, 2022, 52 (06) :4400-4414

[43] An Artificial Bee Colony Algorithm Based on Dynamic Penalty and Levy Flight for Constrained Optimization Problems [J].

Liu, Foxiang ;

Sun, Yuehong ;

Wang, Gai-ge ;

Wu, Tingting .

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (12) :7189-7208

[44] Artificial Bee Colony (ABC) for multi-objective design optimization of composite structures [J].

Omkar, S. N. ;

Senthilnath, J. ;

Khandelwal, Rahul ;

Naik, G. Narayana ;

Gopalakrishnan, S. .

APPLIED SOFT COMPUTING, 2011, 11 (01) :489-499

[45] A Novel Artificial Bee Colony Algorithm for Global Optimization [J].

Yazdani, Donya ;

Meybodi, Mohammad Reza .

2014 4TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE), 2014, :443-448

[46] Parallel Optimization Based on Artificial Bee Colony Algorithm [J].

Li, Debo ;

Feng, Yongxin ;

Zhong, Jun ;

Zhou, Jielian ;

Yin, Libao ;

Zhou, Junhao .

2017 IEEE 2ND INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA), 2017, :955-959

[47] Modeling and simulation of improved artificial bee colony algorithm with data-driven optimization [J].

Zhang, Mei ;

Tan, Ying-Tong ;

Zhu, Jin-Hui ;

Chen, Yi-Nong ;

Liu, Hai-Ming .

SIMULATION MODELLING PRACTICE AND THEORY, 2019, 93 :305-321

[48] An improved global best guided artificial bee colony algorithm for continuous optimization problems [J].

Yongcun Cao ;

Yong Lu ;

Xiuqin Pan ;

Na Sun .

Cluster Computing, 2019, 22 :3011-3019

[49] A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization) [J].

Sag, Tahir ;

Cunkas, Mehmet .

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2016, 24 (04) :2349-+

[50] Artificial bee colony algorithm with gene recombination for numerical function optimization [J].

Li, Genghui ;

Cui, Laizhong ;

Fu, Xianghua ;

Wen, Zhenkun ;

Lu, Nan ;

Lu, Jian .

APPLIED SOFT COMPUTING, 2017, 52 :146-159

← 1 2 3 4 5 →