A new hybrid optimization method combining artificial bee colony and limited-memory BFGS algorithms for efficient numerical optimization

作     者：Badem, Hasan Basturk, Alper Caliskan, Abdullah Yuksel, Mehmet Emin 

作者机构：Kahramanmaras Sutcu Imam Univ Dept Comp Engn Kahramanmaras Turkey Erciyes Univ Dept Comp Engn Kayseri Turkey Iskenderun Tech Univ Dept Biomed Engn Antakya Turkey Erciyes Univ Dept Biomed Engn Kayseri Turkey 

出 版 物：《APPLIED SOFT COMPUTING》 (应用软计算)

年 卷 期：2018年第70卷

页      面：826-844页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Artificial bee colony algorithm L-BEGS Global optimization Swarm intelligence 

摘      要：In this paper, a new optimization method, which is developed especially for optimization of functions with a large number of local minima, is presented. The proposed method is a hybrid optimization algorithm which employs the artificial bee colony (ABC) and limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithms for combining their powerful features. The most prominent feature of the proposed method over other methods is that it provides accurate results and valuable convergence speeds, as well as easy implementation at the same time. Extensive simulation results supported by detailed statistical analyses show that the proposed method can be used for efficient optimization of functions including well-known benchmark functions and CEC2016 competition functions. (C) 2018 Elsevier B.V. All rights reserved.