Improvement And Application Of Invasive Weed Optimization Algorithm

As the development of the times,intelligent optimization algorithm has been widely applied to many fields because of its strong robustness,fast convergence speed and high optimization accuracy.The mainly study of this paper is the invasive weed optimization algorithm in intelligent optimization algorithm.There are many advantages of the invasive weed optimization algorithm,including simple structure,few parameters,easy to understand and has outstanding global search ability.Therefore,many foreign and domestic scholars began to study the algorithm.But it has not been developed mature yet,and it has some shortcomings,including convergence speed is slow,local optimization is easy to fall into,and optimization accuracy in the later stage is not high.In order to solve these problems,the invasive weed optimization algorithm is improved by this paper,and the improved algorithm is applied to solve the robot path planning problem and the wireless sensor network coverage optimization problem.The main contents of this paper are as follows:(1)The following three improvement solutions are proposed for the standard invasive weed optimization algorithm: firstly,the improved point set is used to construct the initial population in the initialization stage in order to increase the diversity of the population,meanwhile,the improved point set is the combining of the good point set and the random point set;secondly,the improved tent chaotic map is introduced to control the diffusion process of the offspring in the spatial diffusion stage;thirdly,in the later stage of the algorithm,it is integrated to improve the convergence speed and optimization accuracy of the algorithm for the hybrid mutation operator of Cauchy mutation and difference mutation.Finally,through select the six standard test functions,the experiments show that the improved algorithm is easier to jump out of the local optimal solution,and has faster convergence speed and higher optimization accuracy compared with the standard invasive weed optimization algorithm and other commonly used algorithms.(2)The improved algorithm is applied to solve practical problems: it is used to solve the practical problem of the robot path planning and the wireless sensor network coverage optimization for the invasive weed optimization algorithm based on Cauchy mutation.In the robot path planning experiment,we construct the basic environment model,and use the improved algorithm to find the optimal path.The experiment of the robot path planning shows that the path planning with the improved algorithm has better stability,higher planning success rate,and stronger robustness.It has the value of follow-up research.In addition,in the wireless sensor network coverage optimization problem,the experimental results show that the improved algorithm proposed in the paper has higher coverage rate,faster convergence speed,and more uniform sensor node distribution compared with the standard invasive weed optimization algorithm.Therefore,it can further improve the quality of network monitoring,so that the network survival time has been extended.