%0 Journal Article %A LIU Chenghan %A HE Qing %T Adaptive Equilibrium Optimizer Algorithm Combining Oscillating Tabu Search %D 2022 %R 10.3778/j.issn.1002-8331.2106-0063 %J Computer Engineering and Applications %P 68-75 %V 58 %N 10 %X In order to solve the problems of slow convergence speed and easy to be affected by local minimum in the optimization process of equilibrium optimizer(EO) algorithm, an adaptive equilibrium optimization algorithm(CfOEO) combining oscillating tabu search is proposed. Aiming at the problem of slow convergence speed caused by high initial randomness of EO algorithm, elite reverse learning is introduced to initialize the population to increase the searching ability of the algorithm. The local and global search ability of the algorithm is balanced by adjusting the convergence factor adaptively. Finally, an oscillation operator is introduced into the tabu search strategy to improve the ability of the algorithm to leap out of the local minimum. In the simulation experiment, 10 benchmark test functions, some CEC2014 test functions and the Wilcoxon rank sum test of the standard test functions are used to test the optimization performance of the CfOEO algorithm. The test results verify the robustness of the CfOEO algorithm. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2106-0063