A Parameter Adaptive Artificial Bee Colony Algorithm for Real-Parameter Optimization

Jian feng Qiu, Ji wen Wang, Dan Yang, Juan Xie, Nan zhen Yao

Abstract


A new adaptive variant of Artificial Bee Colony algorithm, PAABC, is proposed to improve optimization performance and enhance the robustness of ABC algorithm by incorporating into searching strategy and updating control parameter of searching equation adaptively . The incorporation of the information is helpful to accelerate convergence while avoiding prematurity especially multimodal problem. According to the characteristic of optimization problem, the control parameter will be update adaptively. The better parameter value associated with the mean of the p% best individual will survive into the next generation. Experiment results show that PAABC is better or equal to evolutionary algorithm according to a set of basic test function and the CECâ??13 test suite.

Full Text:

PDF



International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
Creative Commons License
Indexing:
Scopus logo Clarivate Analyatics ESCI logo IET Inspec logo DOAJ logo DBLP logo EBSCO logo Ulrich's logo Google Scholar logo MAS logo