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Wireless Sensor Networks (WSNs) provide wide reach and coverage at low-cost which enable them to be utilized in various fields such as health, smart grid, industrial facilities and defense. One of the fundamental limitations of WSNs in long-lasting applications is the network lifetime. To overcome the battery constraint of sensor nodes, duty cycling, energy-efficient protocols and energy harvesting have been considered widely in the literature. A recently emerging energy harvesting technique, namely Radio Frequency (RF)-based wireless energy transfer promises to extend the lifetime of Wireless Rechargeable Sensor Networks (WRSN) with no dependency on intermittent ambient energy resources. In RF-based wireless energy transfer, deploying power transmitters to fixed locations is costly due to range limitations of wireless power. For this reason, mobile power transmitters that visit a few selected locations; i.e. landmarks are employed. Furthermore, in WSNs sensors are expected to perform certain tasks or missions during their lifetime. The achievement of each mission provides certain profits. In this paper, we aim to optimally select the landmarks for sensor nodes that participate in profit maximizing missions. We propose an Integer Linear Programming (ILP) model, namely Mission-Aware Placement of Wireless Power Transmitters (MAPIT) that optimizes the placement of RF-based chargers in the WRSN by maximizing the number of nodes receiving power from a landmark and those that contribute the maximum profit by achieving a mission. We show that the profit increases for low landmark limit since the number of nodes receiving power from a landmark increases under less landmarks. On the other hand, profit reduces by increased number of missions since the nodes participating to missions become spatially diverse.