Research On Cooperative Artificial Bee Colony Algorithm Based On Homogenized Chebyshev Mapping

With the wide application of optimization problems in theoretical research and engineering practice,swarm optimization based artificial swarm algorithm has become one of the hot research topics.Classical artificial swarm algorithm has the advantages of simple steps,weak parameter dependence and high execution efficiency,and is suitable for dealing with complex nonlinear problems.However,the algorithm has some shortcomings in global development,neighborhood boundary division and convergence efficiency.Therefore,it has important theoretical and practical significance for the further improvement of artificial swarm algorithm.Chaos is a kind of motion mode with rich spatio-temporal dynamic characteristics.Its motion trajectory reflects the characteristics of chaos such as randomness,ergodicity,sensitivity of initial value and unpredictability.With the in-depth study of chaos,the behavior of chaos has penetrated into the fields of physics,meteorology,finance and information.In recent years,the research and application of chaos theory in swarm intelligence algorithm,spread spectrum communication and network security have become more and more popular.In this paper,based on the in-depth study of Chebyshev mapping,the uneven distribution of chaotic mapping and the shortcomings of classical artificial swarm algorithm are systematically analyzed and optimized,and some research results are obtained.The main work and innovation points of this paper are as follows:(1)This paper constructs a Chebyshev mapping system based on homogenization distribution.In order to meet the needs of the range homogenization distribution,the homogenization adjustment function was first derived based on the probability density function of Chebyshev mapping,and then a new system equation was constructed by combining it with the original mapping.Furthermore,the system is simulated by numerical distribution frequency diagram,information entropy,approximate entropy,discrete entropy,K entropy,equilibrium and related characteristics.To sum up,the analysis shows that the new system has better uniform distribution characteristics,lower balance and lower sequence complexity than the similar system,indicating that the homogenization regulation in this paper effectively improves the chaotic characteristics of the original map,laying a foundation for the next specific application.(2)This paper proposes an artificial swarm algorithm that integrates collaborative acquisition control.To increase the efficiency of the artificial colony algorithm iterative accumulation,pioneering global and local optimization ability,this paper analyzes the actual process of honey bees release tracer pheromones,near and nonlinear search behavior and good at using sporadic nectariferous diligence acquisition mechanism,found that bees by adding a logo that in the short term the search area and quadratic programming search area,avoid the repeated search themselves and buzzers,greatly improve the acquisition efficiency.Therefore,this paper USES the independent correlation characteristics of chaotic time series to imitate the collection and control strategy of bee,and proposes a collaborative artificial swarm algorithm.In this paper,the homogenization Chebyshev mapping is introduced to generate the feasible solution of uniform distribution with correlation.Secondly,the chaotic ergodic search is carried out in the neighborhood region which is closely combined with honey source and relatively independent.Finally,by evaluating the optimal solution of different characteristic functions,the experimental results show that the algorithm achieves the improvement of convergence performance,the accuracy of the optimal solution and the optimization efficiency under the condition of limited swarm individuals.Based on the homogenization Chebyshev mapping,a new nonlinear system is constructed according to the distribution theorem of random variable function,and its performance is analyzed in detail.Then it is integrated into the optimization and improvement of artificial swarm algorithm.The results show that the cooperative swarm algorithm has better convergence,stability and accuracy in solving nonlinear problems.