Research On Optimization Algorithm Of Pigeons And Its Application

Pigeon swarm optimization algorithm is a new heuristic algorithm,which was first proposed by Professor Duan Haibin and others in 2014.The pigeons algorithm is to simulate the process of pigeons use the earth's magnetic field and combined homing to the landmark.The algorithm has the advantages of relatively simple principle,few parameters to be adjusted and easy to implement.There are relatively simple calculation,strong robustness and other significant advantages,compared with other parts of the algorithm is also the advantages of faster convergence.At the same time,there are still some deficiencies in the algorithm,which has some disadvantages,such as low convergence precision,easy to appear local optimum,poor stability and so on.Therefore,the theory and application of swarm optimization algorithm is to be studied more deeply and more widely.This paper aiming at the shortage of pigeon swarm optimization algorithm are carried out,to improve the pigeons algorithm from the convergence factor,location factor,add speed factor and subgroup mutation strategy etc.,also the improved algorithm was applied to the practical optimization problems.The main contents of the work will be summarized as the following 3 aspects:(1)the algorithm is improved by adding convergence factor,increasing position factor and velocity factor.It can not only enhance the vitality of the dove,but also improve the diversity of the dove population,and can effectively avoid the premature convergence of the pigeon.The optimization of the relevant standard function of the improved algorithm is completed.(2)the pigeon swarm optimization algorithm is improved by adding a subgroup of mutation strategy,the ideological subgroups mutation strategy applied to pigeon swarm optimization algorithm,overcome the pigeon swarm optimization algorithm premature convergence,but also increases the search space of potential dove population.In order to enhance the local search ability of the algorithm,the greedy strategy is introduced,and the improved algorithm is applied to solve the 0-1 knapsack problem.(3)through the combination of the swarm optimization algorithm and simulated annealing algorithm.According to the characteristics of the algorithm not only has the pigeons algorithm,can also be transferred according to the probability of inferior to,and with a certain probability to accept inferior solutions,can make the pigeons algorithm out of local optimal solution,so as to achieve the objective of global optimum.On the basis of the fusion with the algorithm,the adaptive temperature decay coefficient is introduced into the pigeon swarm optimization algorithm,which can automatically adjust the search conditions according to the current environment,so as to improve the search efficiency.This chapter also improved Gequn algorithm is applied to unmanned submersible path planning problem,in order to increase the scope of application of the improved pigeon swarm algorithm,it also shows that the algorithm is effective and feasible.