In hybrid additive manufacturing (HAM), toolpaths affect the volume building and removing during the sequential or iterative hybrid processing since they control the deposition nozzle or cutting tools. In sequential hybrid additive manufacturing, toolpaths for additive manufacturing module define the volume directly determines of the shape accuracy and volume building time. In this paper, we report a new toolpath generation and optimization method for a developing cold spraying-based HAM process's additive processing module. This method adopts a valid physical deposition profile to set scanning parameters and then applies an evolutionary optimization algorithm to minimize the total scanning length for building a set of ordered disconnected volumes on a predefined base. The propose method is illustrated by a complex tree shape model and validated by three selected numerical examples. It has potential to help save spraying raw materials and time as well as improve shape accuracy.