Research On Improvement And Application Of Ant Lion Algorithm

Ant lion algorithm is a class of swarm intelligent optimization algorithms inspired by the hunting behavior of ant lions in nature.Ant lion algorithm simulates ant lion larvae ’behaviors such as constructing traps,ant random walking,and ant lion hunting ants,and has global search capabilities.Ant lion algorithm,as a new type of bionic swarm intelligent optimization algorithm,has the advantages of simple principle,easy to use,high search efficiency and convergence accuracy.In this paper,based on previous research,the ant lion algorithm is improved and used to solve engineering design,PID parameter optimization,and wireless sensor network coverage optimization problems.The main work of this article is as follows:(1)Aiming at the problems of local optimization and low population diversity in the basic ant lion algorithm,a multi strategy improved ant lion algorithm was proposed.Aiming at the shortcomings of the basic ant lion algorithm,this algorithm uses the mutation mechanism of Levy flight to perform mutation operations on the location update method of ant random walk,which can expand the search space of ants and increase the diversity of ants.At the same time,it introduces the sine cosine algorithm into the elite ant lion location update method to coordinate the local search and global search capabilities of the algorithm.The effectiveness of the proposed algorithm is verified through optimization experiments on typical test functions,and good application results are obtained on PID parameter optimization problems.(2)Aiming at the problem that the basic ant lion algorithm has insufficient exploration ability and the ability of global search and local search is unbalanced,a chaotic ant lion optimization algorithm based on quadratic interpolation is proposed.The algorithm introduces logistics chaotic map on the basis of the basic ant lion algorithm.On the one hand,it is improved and used to initialize the population to enrich the ant lion and ant population;On the other hand,chaos is used to improve the position of ants to improve the development ability of the algorithm when ants swim around the ant lion,and quadratic interpolation method is introduced to improve the position update mode of elite ant lion to coordinate and improve the global exploration and local development ability of the algorithm.(3)The improved ant lion optimization algorithm is applied to the coverage optimization problem of wireless sensor networks.Through comparative experimental analysis,the feasibility of the improved ant lion optimization algorithm is verified.