A Hybrid Algorithm Based On Genetic Algorithm And Ant Colony Algorithm For Wireless Sensor Network Location

Wireless sensor network technology is widely used in all walks of life,has been written in the thirteen Five-Year Plan,is a national strategic technology,and location information is the key information of wireless sensor networks,most applications rely on node location,positioning solution will promote the wider use of wireless sensor networks,will also facilitate other industries,is conducive to national economy and people's livelihood.In order to solve the localization problem,I have studied a large number of documents and carried out many experiments.Finally,based on the previous research,this paper presents a hybrid algorithm based on genetic algorithm and ant colony algorithm.The genetic algorithm uses real-coded,linear and non-uniform mutation operator.Based on the search results of the genetic algorithm,the improved ant colony algorithm is used for further searching.The ant colony algorithm adopts the MMAS algorithm to generate the initial attraction intensity distribution according to the genetic algorithm search result.Then use the form of Gaussian distribution in the initial solution neighborhood search,and then apply the elite strategy hybrid algorithm to generate new individuals and parents of the population,retaining the optimal individual for a new generation of population.The simulation results show that the hybrid algorithm is better than the traditional localization algorithm such as dv-hop and genetic algorithm,and the convergence of the algorithm is better than that of the genetic algorithm and ant colony algorithm.The hybrid algorithm has the advantages of two algorithms,High positioning accuracy,fast convergence speed,is an excellent wireless sensor network localization algorithm.The algorithm proposed in this paper has certain reference to the research and improvement of the localization algorithm.The excellent properties of the hybrid algorithm show that the combination of excellent algorithms will be an alternative method to solve the localization problem and even the optimization problem.