Advancing Satellite Communications: Multi-Objective Optimization with Genetic Algorithms

This study explores dynamic resource allocation strategies for multi-beam satellite communication systems, focusing on optimizing communication delay, packet loss, and power consumption. We conduct a detailed comparative analysis of various Genetic Algorithm (GA) variants, such as NSGA-II and SPEA2, to address the multi-objective optimization problem inherent in resource allocation. This research advances multi-beam satellite resource management, offering an adaptable optimization technique balancing key performance factors like latency, loss, and power usage.