Hybrid optimization algorithm of PSO and ABC

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (35): 32-34.

• 研究、探讨 • Previous Articles Next Articles

Hybrid optimization algorithm of PSO and ABC

LIU Junfang1，ZHANG Xueying1，NING Aiping1，2

1.Department of Information Engineering，Taiyuan University of Technology，Taiyuan 030024，China
2.Department of Electronic Information Engineering，Taiyuan University of Science and Technology，Taiyuan 030024，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-12-11 Published:2011-12-11

PSO和ABC的混合优化算法

刘俊芳1，张雪英1，宁爱平1，2

1.太原理工大学信息工程学院，太原 030024
2.太原科技大学电子信息工程学院，太原 030024

Abstract

Abstract: This paper proposes a parallel hybrid optimization algorithm of ABC-PSO by combining Particle Swarm Optimization（PSO） algorithm and Artificial Bee Colony（ABC） algorithm.In each iteration，the swarm is divided into two sub-groups，one sub-group evolves using PSO algorithm，the other sub-group evolves using ABC algorithm and then the two algorithms are compared after selecting the best fitness value.Through comparing the hybrid algorithm with the standard PSO algorithm in evolving solution to four standard functions，the results show that the ABC-PSO hybrid algorithm has a better optimization performance.

Key words: Particle Swarm Optimization（PSO） algorithm, Artificial Bee Colony（ABC） algorithm, ABC-PSO hybrid algorithm, swarm intelligence

摘要： 通过将粒子群优化（Particle Swarm Optimization，PSO）算法与人工蜂群（Artificial Bee Colony，ABC）算法相结合，提出一种ABC-PSO并行混合优化算法。在每次迭代中，将种群分为两个子种群，一个子种群使用PSO算法，另一个子种群使用ABC算法，两个算法寻优后进行比较，选出最优适应值。通过混合算法对4个标准函数进行测试，并与标准PSO算法进行比较，结果表明混合算法具有更好的优化性能。

关键词: 粒子群优化算法, 人工蜂群算法, ABC-PSO混合算法, 群体智能

LIU Junfang1，ZHANG Xueying1，NING Aiping1，2. Hybrid optimization algorithm of PSO and ABC[J]. Computer Engineering and Applications, 2011, 47(35): 32-34.

刘俊芳1，张雪英1，宁爱平1，2. PSO和ABC的混合优化算法[J]. 计算机工程与应用, 2011, 47(35): 32-34.

[1]	WANG Jiayue, SHI Li. Research on Path Optimization and Charging Strategy of Electric Refrigerated Vehicle Considering Cost of Battery Capacity Degradation [J]. Computer Engineering and Applications, 2021, 57(24): 283-289.
[2]	LIAO Weilin, CHENG Shan, SHANG Dongdong, WEI Zhaobin. Particle Swarm Optimization Algorithm Integrated with Multiple-Strategies [J]. Computer Engineering and Applications, 2021, 57(1): 69-76.
[3]	HONG Tianlong, XIE Lijun, HE Lisha, NI Zhongyi, ZHENG Yao. Auto Tunning for In-Situ Volume Depth Image Generation Based on Particle Swarm Optimization Algorithm [J]. Computer Engineering and Applications, 2019, 55(11): 237-243.
[4]	ZHANG Weican, HE Xuansen. Underdetermined blind source separation based on improved bee colony clustering [J]. Computer Engineering and Applications, 2018, 54(17): 243-248.
[5]	HUANG Yafei, WANG Guofu, ZHANG Faquan, YE Jincai. Image denoising method based on bee colony algorithm and parametric threshold function [J]. Computer Engineering and Applications, 2018, 54(17): 164-168.
[6]	MAO Sheng1，2, XIE Wenjun1, ZHANG Jianye1, ZHAO Xiaolin1. Double evolutional artificial bee colony algorithm for solving vehicle routing problem [J]. Computer Engineering and Applications, 2016, 52(7): 35-42.
[7]	SHI Xianming, LIU Yi’an. Digital modulation recognition method based on MPSO optimizing BP neural network [J]. Computer Engineering and Applications, 2016, 52(17): 133-139.
[8]	YUAN Liqiao, YANG Xiwang, YANG Mengru. Research on QoS routing algorithm based on PSO classified by BP neural network [J]. Computer Engineering and Applications, 2015, 51(9): 98-102.
[9]	LI Rong, SHEN Yunbo, LIU Jian. Improved adaptive Particle Swarm Optimization algorithm [J]. Computer Engineering and Applications, 2015, 51(13): 31-36.
[10]	CHEN Jiumei1，2, GONG Ying1，2. Artificial Bee Colony algorithm with variable neighborhood search for two-Echelon Location-Routing Problem [J]. Computer Engineering and Applications, 2014, 50(6): 25-30.
[11]	SHENG Xinyi1, SUN Jun2, ZHOU Di1, XU Wenbo2. Quantum-behaved particle swarm optimization method based on Q-learning [J]. Computer Engineering and Applications, 2014, 50(21): 8-13.
[12]	SHENG Xinyi1, SUN Jun2, ZHOU Di1, XU Wenbo2. Self-learning quantum-behaved particle swarm optimization algorithm [J]. Computer Engineering and Applications, 2014, 50(20): 24-29.
[13]	ZHAO Yu, SUN Ting. Wireless indoor location method based on PSO-SVM [J]. Computer Engineering and Applications, 2014, 50(19): 95-98.
[14]	LI Junwu, YU Zhifu. Improved PSO and its application to DOA estimation [J]. Computer Engineering and Applications, 2013, 49(9): 203-206.
[15]	GONG Guobin. Adaptive constrained optimization hybrid Particle Swarm Optimization algorithm [J]. Computer Engineering and Applications, 2013, 49(9): 50-53.

Hybrid optimization algorithm of PSO and ABC

PSO和ABC的混合优化算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics