A Modified Artificial Bee Colony Algorithm for Function Optimization Strategy

Joint Conference on Green Engineering Technology & Applied Computing 2019

工业技术（总论）;计算机科学

Chen, Chang-Feng^1 ; Daud, Nasarudin Bin^1 ; Zhou, Kai-Qing^2 ; Elisha Nyamasvisva, Tadiwa^1

Faculty of Engineering, Science and Technology, Infrastructure University Kuala Lumpur, Kuala Lumpur

43000, Malaysia^1

College of Information Science and Engineering, Jishou University, Jishou, Hunan

416000, China^2

关键词: Approximate solution;    Artificial bee colony algorithms;    Artificial bee colony algorithms (ABC);    Complex optimization problems;    Faster convergence;    Function Optimization;    Global search ability;    Standard test functions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/551/1/012029/pdf
DOI  :  10.1088/1757-899X/551/1/012029

来源: IOP

【 摘 要 】

Artificial Bee Colony (ABC) algorithm has received wide attention due to the outstanding performance in solving complex optimization problems. However, the further application of ABC is still hindered due to some bottlenecks, such as slow convergence velocity, poor global search ability and low accuracy of solution. To overcome these problems, an improved ABC (CT-ABC) is proposed in this paper by using both a chaotic map and a tolerance based search equation (TSE). Some standard test functions are chosen to verify the performance by implementing the proposed modified ABC algorithm, basic ABC and another modified ABC (WABC). Simulation results reveal the proposed CT-ABC algorithm is able to obtain the faster convergence speeds and better accurate approximate solution.