Optimization of Multi-Objective Coverage Strategy Based on Multiple Particle Swarm Coevolutionary Algorithm for Water Environment Monitoring System

Hong Wei Zhao; Li Wei Tian

doi:10.4028/www.scientific.net/AMM.742.360

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 742Optimization of Multi-Objective Coverage Strategy...

Optimization of Multi-Objective Coverage Strategy Based on Multiple Particle Swarm Coevolutionary Algorithm for Water Environment Monitoring System

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volume 742)

Pages:

360-363

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.742.360

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Online since:

March 2015

Authors:

Hong Wei Zhao*, Li Wei Tian

Keywords:

Co-Evolution, Particle Swarm, Swarm Intelligence, Water Environment Monitoring

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