Exploiting mobile elements (MEs) to accomplish data collection in wireless sensor networks (WSNs) can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps: we first construct a virtual grid network and select the minimal stop point set (SPS) from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm (GA) are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency. Exploiting mobile elements (MEs) to accomplish data collection in wireless sensor networks (WSNs) can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data we critically applications for two steps: we first construct a virtual grid network and select the minimal stop point set (SPS) from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm (GA) are used to solve the problem. reduce the traveling length of MEs, and decrease the data collection latency.