Personal perception network structure optimization method based on improved snake vulture algorithm

Abstract

The invention discloses a presence / absence perception network structure optimization method based on an improved snake vulture algorithm, and the method comprises the steps: building a multi-target optimization model according to a heterogeneous presence / absence collaborative perception network structure based on the degree of nodes and the average value of the reciprocal of the shortest path between node pairs, initializing the parameters of the improved snake vulture algorithm, and carrying out the optimization of the multi-target optimization model. An upper triangular coding method is adopted to form individuals in the population, and Tent chaotic mapping is introduced. Solving the multi-objective optimization model by using an improved snake vulture algorithm, and updating the position and fitness value of the individual through two escape strategies of the snake vulture; gaussian and Cauchy variation disturbance is introduced to help the algorithm jump out of local optimum and search towards a globally optimal solution; a greedy strategy is introduced, and the algorithm is guided to keep tracking of an optimal solution in the search process by comparing fitness values. According to the invention, the optimal heterogeneous presence / absence cooperative sensing network structure under different tasks can be obtained, and the overall efficiency of the presence / absence system is improved.