Abstract: In wireless sensor networks, in order to reduce energy holes, the node data is collected by planning the shortest path of mobile sink.This problem is considered as a special case of traveling salesman problem (TSPN) with neighborhood.Since the problem has no polynomial time solution, a hybrid immune particle swarm optimization (HIPSO) algorithm is proposed by combining the immune algorithm with the simulated annealing particle swarm algorithm to solve the approximate solution of the problem.In this algorithm, the wireless sensor network is modeled as a communication range for the size of the circular area, sink network and mobile sensor nodes within the range of the data acquisition, the establishment of energy and moving path model, using HIPSO algorithm to solve the optimization model, the sink node moving path of the minimum energy consumption obtained.Simulation results show that the approximate solution obtained by this algorithm can reduce energy consumption and prolong the network life cycle compared with other algorithms.