Chicken swarm optimization algorithm is a new swarm intelligent optimization algorithm proposed by Meng et al in 2014.CSO algorithm is mainly through the classification of chicken species,and then the establishment of chicken hierarchy system for optimization.Chicken swarm optimization algorithm has the advantages of few control parameters and high stability,and is used to solve various optimization problems.However,in terms of its own iteration mechanism,the chicken swarm optimization algorithm has some shortcomings,such as falling into local optimum too early and poor accuracy in solving optimization problems in the late iteration period.Therefore,the chicken swarm optimization algorithm has great research potential.The main content of this paper includes three aspects:(1)For unconstrained optimization problems,The chicken swarm optimization algorithm has some disadvantages such as low accuracy and easy to be trapped into local optimization.An improved chicken swarm optimization algorithm(ICSO)based on Levy flight strategy and nonlinear decrement strategy was proposed.In this algorithm,Levy flight strategy is introduced into the hen position update formula and nonlinear decreasing strategy is introduced into the chicken position update formula to enhance the later optimization ability of the algorithm.the ICSO algorithm is numerically tested,PSO algorithm and CSO algorithm.The results show that the accuracy and speed of ICSO algorithm are greatly improved for eight test problems.Finally,the ICSO algorithm is applied to the robot path planning problem,and the results show that the improved chicken swarm optimization algorithm can find a shorter robot path.(2)In order to solve the complex unconstrained continuous optimization problem,the basic chicken swarm optimization algorithm has the disadvantages of low precision and great search blindness.At the same time,in view of the update mechanism of chicken swarm optimization algorithm itself,that is,when the hen is no longer close to the global optimal position,the chicks affected by the hen are no longer close to the optimal position.An improved chicken swarm optimization algorithm based on Levy flight and contraction factor strategy is proposed In this algorithm,Levy flight strategy is introduced into the hen position formula and contraction factor strategy is combined in the chicken position formula to improve the local search ability in the later stage of the algorithm.Through the numerical experiments of eight test problems,the accuracy and stability of LCSO algorithm are greatly improved compared with the basic chicken optimization algorithm.Finally,the improved chicken swarm optimization algorithm(LCSO)is applied to the emitter location problem,and the results show that the improved algorithm can locate the emitter more accurately.(3)For constrained optimization problems,based on the improved chicken swarm optimization algorithm based on Levy flight and contraction factor strategy,an improved chicken swarm optimization algorithm combined with penalty function(PF-LCSO)is proposed.Firstly,constrained optimization problems are transformed into unconstrained optimization problem,and then the second part of the improved chicken swarm optimization algorithm(LCSO)is used to solve the unconstrained optimization problem Optimization problem.Six standard constrained optimization problems are used for numerical experiments,and the results show that PF-LCSO algorithm has higher accuracy and stronger stability than other constrained optimization algorithms.Finally,the PF-LCSO algorithm is applied to the practical engineering problems of pressure vessel design.The results show that the PF-LCSO algorithm can achieve lower cost and better solve the problem of pressure vessel design. |