Abstract: Drying has been widely used to provide a longer shelf life for various agricultural products. The moisture content can be reduced to prevent the spoilage of harvested agricultural products, in order to inhibit the growth of bacteria, yeasts, and molds. Among them, the drying system of solar-assisted air source heat pumps has drawn much attention in recent years, due to excellent energy saving and high dried quality of products. However, solar energy can be badly wasted, when the water tank temperature cannot meet the drying requirement, because of the high drying temperature during the middle and last drying stage. In this study, a solar-assisted multi-heat source heat pump (SMSHP) drying system was proposed to incorporate a water-source evaporator into the existing solar-assisted air source heat pump drying system, in order to improve the economic, and environmental benefit and the utilization rate. The fuzzy analytic hierarchy process was used to develop the optimization model of the SMSHP drying system. The optimization variables were selected as the collector inclination Angle, collector area, water tank volume, heat pump power, water pump flow rate, and airflow rate. The economy, system performance, and energy efficiency were chosen as the optimization objectives of the model. After that, the multi-objective optimization function of the SMSHP drying system was established to obtain a total of 25 groups of optimal combinations after the orthogonal test. Moreover, the simulation model of the SMSHP drying system was developed using the TRNSYS software. The accuracy of the model was verified, according to the experimental platform. Then the 25 groups of optimal combination parameters were introduced into the TRNSYS simulation model of the SMSHP drying system. The optimal parameter group was obtained with the highest system performance. Finally, the optimal and original parameter sets were compared and analyzed to verify the practicability and reliability of the model. The results showed that only 20 groups of 25 optimization parameters met the requirements of the drying process. The relative humidity of the air in the drying room was too high to meet the system requirements in the rest 5 groups. The economy, system performance, and energy efficiency were compared on the 25 groups' optimization. The optimization objective function of the 10th group was the lowest, indicating the optimal objective function. In addition, the TRNSYS simulation also showed that the optimal combination of parameters met the requirement of the drying process. The optimization parameter group 10 was the optimal one. The optimal parameters were obtained: the collector inclination angle was 35 °, the collector area was 40 m², the water tank volume was 1.5 m³, the heat pump power was 10 kW, the water pump flow rate was 2 700 kg/h, and the airflow rate was 3 500 m³/h. Compared with the TRNSYS simulation of the original and the optimal parameters, the cost of the SMSHP drying system was reduced by 4.78%, whereas, the system performance and energy saving were improved by 17.08%, and 9.41%, respectively. All indicators were comprehensively improved by 6.27%. The multi-objective optimization of the solar multi-heat source heat pump drying system was carried out using a fuzzy analytic hierarchy process and TRNSYS simulation analysis. The finding has an important guiding significance to improve the performance of solar combined heat pump drying systems.