The performance of improved invasive weed optimization algorithm (IIWO) and its application for coverage optimization in wireless sensor networks were discussed.On the premise that connectivity among nodes was guaranteed,a mathematical model was established to achieve the coverage of objective area with wireless sensor networks.This problem was transformed into function optimization based on this algorithm.Then, the invasive weed optimization algorithm was used to search the optimal deployment with the strong search performance.The cubic mapping chaotic operator was introduced to enhance the ability of local search and robustness, and the Gauss mutation operator was used to keep the diversity of population.Lastly, the proposed algorithm was verified through the numerical benchmark functions and coverage simulation.All the results show that the proposed algorithm has fast convergence speed, nice robustness and strong ability of data mining.Hence, it has the ability to solve the problem of deployment problem in wireless sensor networks.