Coverage optimization for WSNs based on improved genetic algorithm
A multi-objective genetic algorithm based on inverse model guided algorithm search(MOEA-OMG)is proposed,which obtains the experimental solution containing the distribution information of the population by random sampling of objective space of the population,and then mapping the sampled solution back to the decision space by using Gaussian process,guides the algorithm search,and produces high-quality offspring solutions by combining the trival vector solution with the other solution individuals by using the proposed recombination operator.The algorithm is applied to solve the WSNs coverage problem and experimentally compared with several traditional optimization algorithms,and the results show that the designed algorithm based on the inverse model-guided search shows more obvious performance advantages in solving the WSNs coverage problem.
万方数据
维普
