Optimization of multi-objective coverage strategy Based on Multiple Particle Swarm Coevolutionary Algorithm for Water Environment Monitoring System

摘要

This paper built a multi-objective optimization model and proposed an improved multi-objective particle swarm optimization algorithm called MPS2O, which is based on Multiple Particle Swarm Co-evolutionary. The MPS2O algorithm has considerable potential for solving multi-objective optimization problems. Mathematical benchmark functions also shows that the proposed algorithm is an excellent Alternative for solving multi-objective optimization problems. Making full use of the research findings home and abroad, MPS2O has been chosen to be the coverage optimization strategy of the wireless sensor networks in Water Environment Monitoring System. Simulation results demonstrate that the MPS2O algorithm is more efficient than the PSO algorithm in solving this real-world problem.