To address the problem of inefficient resource allocation during task offloading in mobile edge computing (MEC) environments for terminal devices, a multi-task partial offloading scheme is proposed that leverages device-to-device (D2D) communication technology to assist the MEC system. The scheme is based on the block coordinate descent (BCD) method to optimize the task offloading and resource allocation strategies jointly. Additionally, a dynamic pricing strategy is adopted to incentivize the service-oriented smart devices (SSDs) to share the remaining available computational resources, aiming to minimize the system-wide execution cost. Firstly, the reconfiguration linearization technique (RLT) and convex optimization theory are utilized to optimize the allocation of computational resources and the offloading ratios, determining the tasks to be allocated to local computing, D2D offloading and edge offloading. Secondly, the appropriate SSDs are selected to perform D2D offloading tasks based on the optimal offloading policy. Simulation results show that, compared with the traditional partial offloading scheme, relay-assisted offloading scheme, and cooperative computing offloading scheme, the proposed offloading scheme reduces the total cost of system execution by 27.62%, 25.58% and 19.98%, respectively, under different numbers of devices, and reduces the total cost of system execution by about 43.35%, 38.19% and 36.79%, respectively, under different conditions of the maximum tolerable delay. The average reduction in total system execution cost under different task data sizes is about 36.47%, 30.60%, and 29.15%, respectively. Further experiments indicate that, compared with the greedy offloading scheme, the proposed offloading scheme optimizes the system execution cost by an average of 7.59%, 0.39% and 3.10% for different numbers of devices, maximum tolerable delays and task data sizes, respectively. Therefore, this scheme effectively enhances the resource utilization while reducing the execution cost.