The path planning scheme for joint charging and data collection in WRSNs: A multiobjective optimization method Abstract   Considering the limited energy of the mobile wireless charging equipment (WCE) in wireless rechargeable sensor networks (WRSNs), strategies for energy replenishment and data collection are proposed. A novel path planning model for the mobile WCE based on multiobjective optimization is constructed to both replenish energy and collect data, as well as to maximize the total energy utility of the mobile WCE and minimize the average delay of data transmission. An algorithm of multiobjective ant colony optimization (ESMOAC) based on the elitist strategy is proposed to determine the Pareto set, so that the state transition strategy and the pheromone updating strategy improve. How the parameter settings of the ant colony algorithm affect the proposed algorithm is analyzed. The results of 50 groups of numerical simulation experiments show that the average of the Pareto set of the ESMOAC algorithm is 27.8% higher than that of the NSGAII algorithm.

Mobile wireless sensor network lifetime maximization by using evolutionary computing methods Abstract   Due to the continuous development and progress of wireless communication technology and sensor network technology, wireless sensor networks (WSNs) have gradually become an attractive technology that facilitates peopleu0027s lives. Due to the extensive use of WSNs, maximizing the lifetime of WSNs to obtain realtime and effective information has become a critical concern. This paper studies the life of mobile wireless sensor networks (MWSNs). MWSNs are a special type of WSN in that the sensor nodes are movable within a certain area. A system model is developed to prolong the network lifetime of MWSNs. This paper uses five evolutionary computing (EC) algorithms to develop the MWSN lifetime optimization model. Numerical simulations are performed to study the advantages and disadvantages of the five algorithms for solving the model. The comparison and discussion can provide advice for using EC algorithms to solve MWSN lifetime maximization problems.