Improved DOA based on the Tent chaos

For the original dingo optimization algorithm (DOA), such as slow convergence rate, easy to fall into local optimal solution, and reduction of population diversity, a dingo algorithm based on Tent chaotic mapping is proposed. Firstly, the uniformity and ergodicity of the Tent chaos mapping are used to ensure the difference of the population average and to improve the convergence rate of the algorithm; secondly, by introducing the scavenger strategy of the group average update position, the population update is not worse than the population average, so as to improve the convergence speed of the algorithm; finally, the weight factor is introduced into the population update strategy to improve the convergence speed and solution accuracy of the algorithm. It can be seen from the eight standard test functions that the multi-strategy improved dingo algorithm has faster optimization speed and stronger optimization ability.