A Novel Adaptive Cooperative Artificial Bee Colony Algorithm for Solving Numerical Function Optimization

被引：1
|
作者：
Liu, Bin [1 ]
Li, Wei-min [1 ]
Pan, Shuai [1 ]
机构：
[1] AFEU, Air & Missile Def Coll, Xian, Peoples R China
来源：
THEORY, METHODOLOGY, TOOLS AND APPLICATIONS FOR MODELING AND SIMULATION OF COMPLEX SYSTEMS, PT I | 2016年 / 643卷
关键词：
Artificial Bee Colony Algorithm; Adaptively narrow search interval; Swarm cooperation; Escaping from local optimum points; Numerical function optimization;
D O I：
10.1007/978-981-10-2663-8_3
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Considering the disadvantages of the traditional Artificial Bee Colony (ABC) Algorithm, a Novel Adaptive Cooperative Artificial Bee Colony (ACABC) Algorithm is proposed in this paper. Some ideas including dividing bee swarm into two parts: main-bee swarm and vice-bee swarm, bringing a judge principle for local optimum points and narrowing bee swarm search interval adaptively are introduced and consequently served as the core of novel Adaptive Cooperative Artificial Bee Colony Algorithm. The performance of PSO, DE, ABC and ACABC algorithms are compared using 10 kinds benchmark testing functions. Simulation results show ACABC owns better optimizing precision and speed and preferable anti-jamming ability, which can be applied for solving other complicated optimization problems.
引用
收藏
页码：25 / 36
页数：12
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