An improved artificial bee colony algorithm based on whale optimization algorithm for data clustering

2020 ◽  
Vol 79 (43-44) ◽  
pp. 32169-32194 ◽  
Author(s):  
Nouria Rahnema ◽  
Farhad Soleimanian Gharehchopogh
Keyword(s):  
Optimization Algorithm ◽  
Data Clustering ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Whale Optimization Algorithm ◽  
Bee Colony ◽  
Whale Optimization

scholarly journals A Novel Optimization Algorithm Combing Gbest-Guided Artificial Bee Colony Algorithm with Variable Gradients

2020 ◽  
Vol 10 (10) ◽  
pp. 3352
Author(s):  
Xiaodong Ruan ◽  
Jiaming Wang ◽  
Xu Zhang ◽  
Weiting Liu ◽  
Xin Fu
Keyword(s):  
Global Optimization ◽  
Optimization Algorithm ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimization Problems ◽  
Numerical Test ◽  
Stochastic Algorithm ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Novel Algorithm

The artificial bee colony (ABC) algorithm, which has been widely studied for years, is a stochastic algorithm for solving global optimization problems. Taking advantage of the information of a global best solution, the Gbest-guided artificial bee colony (GABC) algorithm goes further by modifying the solution search equation. However, the coefficient in its equation is based only on a numerical test and is not suitable for all problems. Therefore, we propose a novel algorithm named the Gbest-guided ABC algorithm with gradient information (GABCG) to make up for its weakness. Without coefficient factors, a new solution search equation based on variable gradients is established. Besides, the gradients are also applied to differentiate the priority of different variables and enhance the judgment of abandoned solutions. Extensive experiments are conducted on a set of benchmark functions with the GABCG algorithm. The results demonstrate that the GABCG algorithm is more effective than the traditional ABC algorithm and the GABC algorithm, especially in the latter stages of the evolution.

A new approach for data clustering using hybrid artificial bee colony algorithm

2012 ◽  
Vol 97 ◽  
pp. 241-250 ◽  
Author(s):  
Xiaohui Yan ◽  
Yunlong Zhu ◽  
Wenping Zou ◽  
Liang Wang
Keyword(s):  
Data Clustering ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
New Approach ◽  
Bee Colony
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