Title :
An Algorithm for Global Optimization Problems Based on ABC-BFGS
Author :
Li, Xiaojing ; Zhao, Huasheng ; Jin, Long
Author_Institution :
Guangxi Coll. for Preschool Educ. Nanning, Nanning, China
Abstract :
To overcome the problem of premature convergence on Artiifcial Bee Colony (ABC) in optimizing multi modal function, this paper proposed a hybrid algorithm of ABC-BFGS, and used a special mutation to make algorithm escape local minima. Four classic multi-valued functions (Rosen Brock, Rastrigin, Griewank, Ackley) were selected as the test functions. The experimental results show that the ABC-BFGS algorithm not only can effectively locate the global optimum, but also have a rather high convergence speed. The ABC-BFGS algorithm is a promising approach for solving global optimization problems.
Keywords :
convergence; evolutionary computation; optimisation; ABC-BFGS; Ackley multivalued function; Griewank multivalued function; Rastrigin multivalued function; Rosen Brock multivalued function; artiifcial bee colony; convergence speed; global optimization problem; hybrid algorithm; local minima; multimodal function optimization; premature convergence; special mutation; Algorithm design and analysis; Convergence; Educational institutions; Electronic mail; Optimization; Particle swarm optimization; Search problems; BFGS method; artiifcial bee colony; global optimum; hybrid algorithm;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-1365-0
DOI :
10.1109/CSO.2012.197