An Improved Artificial Bee Colony Algorithm Based on Faster Convergence

摘要

An improved Artificial Bee Colony (ABC) algorithm was proposed, in order to improve the shortcomings of fast convergence early and easily being caught in local optimum; And slow convergence late and losing variety of solutions, for the solutions updating domain by domain. With the strong ability of multi-domain updating of solution exploration, it can not only strengthens the exploration, but also can enrich the variety of solution, a faster convergence ABC is proposed. Testing the IABC algorithm with standard testing function Ackley, Griewank, Schaffer and Sphere, results show that the algorithm not only fasten the convergence speed, but also improve the optimum found, providing a better optimization performance.