The Improved Cuckoo Search Algorithm And Its Application

Cuckoo search algorithm has received wide attention from domestic and foreign experts and scholars since it was proposed in 2009,they make deeply research and improvement of the algorithm in the performance and application scope,and use it to solve some practical problems.In this paper,the principle of cuckoo search algorithm is introduced first,followed by the Lévy flights mechanism,the specific steps and execution processes of the algorithm.On the basis of analyzing the defects of the basic cuckoo search algorithm,a novel operation to strengthen local search is designed,and two improved cuckoo search algorithms are proposed.Finally,the cuckoo algorithm is applied to the practical problem,vehicle routing problem.The main contributions are summarized as follows:Firstly,aimed at the problem that cuckoo search algorithm shows low convergence rate and poor optimization accuracy in multi-dimensional function optimization.This paper presents a Cuckoo Search based on Acceleration Operator and Refraction Disturbance and designs an acceleration operator to improve the optimum speed.Besides,it brings the refraction disturbance of water wave optimization(WWO)to avoid trapping in local optimum and improve the search precision.The comparison of other improved Cuckoo Search algorithms proves the effectiveness of the algorithm.Secondly,in order to tackle with mlti-dimension function optimization problems,this strategies,as a result of taking the same step and random walk,may reduce the convergence speed and the quality of the solution on the algorithm due to different search capability of every individual.An improved CS algorithm named Dynamic Adaptive Multi-Cuckoo Search Algorithm(DAMCS),is proposed to overcome this shortage.On the basis of the difference of fitness value of the individual,the population of the proposed algorithm consists of one elite sub-population,one ordinary sub-population and one developing sub-population.Each sub-population is evolved with different steps of Levy flights.The step is changed adaptively accordingto different sub-populations and calculation times of fitness.The population of the proposed algorithm consists of one elite sub-population and one developing sub-population by the fitness value of the population after they were spotted.Elite sub-population learns from the best individual to strengthen the local search ability,developing the sub-population evolved with Mutation operator of Differential Evolution(DE)algorithm to overstep the local optimum.Sub-population will be transformed basing on the fitness value in the next iteration,and each sub-population.communicate information well.The experimental results of test functions indicate that DAMCS algorithm behaves stronger performance on convergence as well as adaptation and confirms the effectiveness.Thirdly,in order to better apply cuckoo search algorithm to discrete combinatorial optimization problem,a discrete cuckoo search algorithm for solving vehicle routing problem is proposed.This paper encodes the individual in the cuckoo search algorithm using integer encoding,and produces the initial solutions based on greedy strategy.On the basis of the basic cuckoo search algorithm,the individuals are updated by 2-opt operator and inversion operator instead of levy flights inside the loops.After the individuals are spotted,they are updated by insert operator and exchange operator instead of random walk strategy between the loops.The experimental results of multiple data sets indicate that the performance of the improved algorithm in vehicle routing problem is better than that of other comparative algorithms,and it can be extended to other practical combinatorial optimization problems.