Radio-frequency resources (RFRs) are strategic and fundamental for the construction and operation of space-based information networks. With the rapid evolution and development of integrated space and ground information networks, competition for RFRs is becoming increasingly intense. Following the International Telecommunication Union (ITU) Radio Regulations, the scarcity of available resources is becoming more evident, and the contradiction between supply and demand is exacerbated by the low utilization efficiency of existing RFRs. To address the current issues, this research investigates scheduling problem in units of frequency assignments (FAs) for multiple tasks, where FAs are basic unit of RFRs defined by the ITU. A multi-task scheduling model is built with dual objectives of maximizing task completion and minimizing aggregate interference for other RFRs in priority. An task oriented FAs scheduling approach based on an improved genetic algorithm is proposed optimizing the dual objectives. Through simulation experiments based on the ITU database, the proposed approach significantly enhances two objectives performance compared to alternative scheduling methods.