Ubiquitous computing for human-cyber-physical integration is becoming a new requirement and trend in software development. Based on this new computing paradigm, human-cyber-physical applications further extend software technology to the effective utilization of offline resources, including physical devices and human resources. As a typical human-cyber-physical scenario, the collaboration between the device and human resources in the physical world features resource selectivity, high task frequency, and worker dynamics. Traditional resource scheduling techniques cannot meet the scheduling requirements of this task type (referred to as DHRC task). Thus, this study proposes an optimal scheduling method for collaborative tasks between device and human resources. This method includes two stages of device resource scheduling and human resource scheduling. In the device resource scheduling stage, a device resource scheduling algorithm based on NSGA-II is proposed to optimize task resource selection by comprehensively considering such factors as task distance, device load, and the worker number around the device location. In the human resource scheduling stage, a human resource scheduling algorithm based on DPSO is put forward to optimize the worker selection and corresponding path planning according to such factors as worker location and collaboration dependency. Experiments in a simulated environment show that the algorithm in the first stage is equivalent in efficiency and superior in utility to the compared algorithm (discrete particle swarm optimization algorithm). The algorithm in the second stage is superior in efficiency and utility to the compared algorithm (the genetic algorithm improved by the tournament mechanism).