An improved artificial bee colony algorithm for solving parameter identification problems (Q2224240)

Summary: Swarm intelligence algorithms (SIA) have shown excellent optimisation performance on many real world problems. Artificial bee colony (ABC) is one of the most popular SIA. However, ABC has some shortcomings. In this paper, we design an improved ABC, called IABC, which introduces a hybrid search strategy. To evaluate the optimisation ability of IABC, we run IABC on several famous benchmark functions. Experimental results show that IABC can achieve good solutions on the test functions. Finally, IABC is used to solve parameter identification problems. Two test instances are used for the simulation experiment. Results demonstrate that IABC can obtain a good matching to the target model.