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Meta-optimization for Charger Deployment in Wireless Rechargeable Sensor Networks

This paper proposes the genetic particle swarm optimization charger deployment (GPSOCD) algorithm to deploy as few chargers as possible to fulfill the charging demands of sensors of a wireless rechargeable sensor network (WRSN) to maintain the WRSN sustainability. The proposed GPSOCD algorithm is a meta-optimization algorithm since it uses the genetic algorithm (GA) to encode and optimize the parameters of a particle swarm optimization charger deployment (PSOCD) algorithm. The PSOCD algorithm in turn relies on the particle swarm optimization (PSO) concept for optimizing the charger deployment with the parameters generated by the GA. Simulations are conducted for the performance evaluation of the GPSOCD algorithm. The simulation results show that GPSOCD outperforms other related algorithms.