Localization Algorithm In Wireless Sensor Networks Based On Multi-Objective Particle Swarm Optimization

Based on multi-objective particle swarm optimization, a localization algorithm is proposed to solve the multi-objective optimization localization issues in wireless sensor networks. The multi-objective functions consist of the space distance constraint and the geometric topology constraint. The optimal solution is found by multi-objective particle swarm optimization algorithm. Dynamic method is adopted to maintain the archive in order to limit the size of archive, and the global optimum is obtained according to the proportion of selection. The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping limited archive size by using both global optimal selection operator and dynamic maintaining archive method.