A Modified Artificial Bee Colony Algorithm for Solving Optimization Problems
Wei‐Der Chang, Shan‐Cheng Pan, Ray-Jer Lee, Cheng-Hua Ku · 2014
In this paper, we develop an improved version of artificial bee colony (ABC) algorithm for solving the numerical optimization problem. In the proposed algorithm, the uniformly random number considered in the formula of generating a new food source is replaced by the chaotic random number which is provided from the Chen’s system. To show the feasibility of the proposed scheme, a function minimization problem with constrained conditions is simulated using a large number of different sets of initial conditions. It is concluded from simulation results and comparisons that the proposed method is superior to the general ABC algorithm.