Abstract: In order to optimize the distribution of the time series related to the initial honey source and search method,and further improve the algorithm’s global pioneering and traversal optimization efficiency,a chaos artificial bee colony algorithm based on homogenizing optimization of generated time series is proposed in this paper.Aiming at the problem that the distribution of initial honey sources generated by chaos time series is too concentrated,firstly,based on the principle of maximum entropy,the Logistic chaos mapping is optimized for homogenization,and entropy spectrum analysis and NIST randomness test are used to verify the randomness of the generated time series,so that the initial honey source generated by it can be randomly and uniformly distributed in the entire solution space,which lays the foundation for the global optimization of the algorithm.Secondly,this paper improves the neighborhood search methods according to search strategies from near to far,and uses the homogenizing time series to search for the optimal location of the honey source,so as to improve the traversal speed and convergence accuracy of the proposed algorithm.Finally,the proposed algorithm performs experimental simulation on nine standard test functions.It is compared with other improved artificial bee colony algorithms and optimization algorithms from the convergence curve and optimization results,and the six algorithms are reasonably introduced into the logistics distribution problem to find the shortest path.The results show that the proposed optimization algorithm not only strengthens the homogenization of initial honey sources,but also has a more significant optimization effect.It can jump out of the local optimal and find the global optimal solution accurately and quickly.

Key words: Chaos artificial bee colony algorithm, Entropy spectrum analysis, Logistic homogenization, Neighborhood reconstruction, Optimization of honey source distribution