# A Heterogeneous Multi-Satellite Dynamic Mission Planning Method Based on Metaheuristic Algorithms
## 1 Introduction
Similarly, a cooperative diversity algorithm was proposed to find the best relay with the highest received signal strength when direct communication is insufficient [15]. While this approach reduces complexity and resource consumption, it does not account for differing latency requirements or user priorities, thus limiting its effectiveness in real-world applications where these factors play a crucial role. Moreover, in another study, researchers identified issues, such as non-uniform ground traffic demand distribution and high satellite mobility [16]. They proposed an algorithm to solve the multi-satellite load balancing problem by minimizing traffic disparities between satellites. However, this solution is primarily focused on balancing satellite loads and does not consider the diverse demands of different user groups, satellite mobility, or dynamic visibility changes over time, which are crucial factors in modern satellite communication systems. These limitations highlight the need for more adaptive and flexible resource management solutions, which our approach addresses by dynamically optimizing satellite resource allocation in response to real-time user demands and system conditions. Traditional methods for planning communication tasks in heterogeneous multi-satellite systems have three main drawbacks. 1. Narrow Focus of Current Studies: Most current task planning algorithm studies primarily emphasize Earth observation and communication scenarios, neglecting the optimization of routine communication for a significant number of daily users, such as those relying on constant connectivity for personal or business needs. 2. Lack of Consideration of User Diversity: Existing task planning algorithms often fail to accommodate the diverse demands of different user groups. For instance, they do not prioritize low-latency requirements for real-time applications, such as video conferencing or online gaming, nor do they provide guarantees for high-priority communications needed in emergency situations. 3. Dynamic User Involvement Challenges: Current research does not sufficiently address the complexities introduced by dynamic user involvement. As visibility between satellites and user terminals fluctuates, there is a pressing need for algorithms that can minimize unnecessary handovers. This is crucial for users who depend on continuous, stable connections, as frequent handovers can lead to disruptions in service quality. These limitations are compounded by the dynamic nature of user demands, which requires the framework to adapt in real time to fluctuating priorities and varying latency requirements. Unlike static scenarios where links remain stable, our framework must manage dynamic visibility conditions, as traditional methods relying on static models cannot accommodate rapid changes, leading to inefficiencies and potential communication failures. Furthermore, the heterogeneous characteristics of satellite systems introduce complexities in resource allocation. Different satellites may operate under varying conditions, such as orbital altitude, transmission delay, and communication capabilities. Our framework must effectively coordinate these differences to ensure optimal resource utilization while maintaining quality of service across diverse user groups. This paper aims to overcome these shortcomings by researching task planning methods based on heuristic algorithms that address challenges, ultimately improving the efficiency and reliability of satellite communication systems in complex operational environments characterized by heterogeneous multi-satellite and multi-user dynamic changes. This study's main contributions include the following. 1. Optimized Routine Communication: Improved communication efficiency for daily users, thus bridging a significant gap in the current literature. 2. Dynamic Resource Utilization: Enhanced resource allocation that adapts in real time to diverse user needs, thus minimizing disruptions in service. 3.