Abstract: A method of deploying static auxiliary chargers (ACs) next to somesensor nodes is used to improve the maximum flow from sources to sinks in the network. So, the research formulates a mixed integer linear program (MILP) for the problem and proves that the problem is NP-hard. Firstly, it proposes to use BottleNeck algorithm whichuses path-by-unit and deploys ACs using the lowest energy node-first principleto generate initial population for genetic algorithm. Then the Improved Adaptive Genetic Algorithm (IAGA) is used to simulate the natural evolutionary process and search for the optimal location for deployment of ACs to maximize the flow rate to sinks. The simulation results show that IAGA can effectively increase the maximum flow arriving at the sinks compared with some other algorithms of distributing ACs.