Joint observation and transmission scheduling of multiple agile satellites with energy constraint using improved ACO algorithm

The problem of joint observation and transmission scheduling with energy constraint is very important, but has received limited attention so far. To address the joint scheduling problem considering energy consumption and supplement, a new constraint satisfaction model with energy constraint for multiple agile satellites is established. Then a Local Search Enhanced Ant Colony Optimization with Multi-Knapsack Task Assignment (LSE-ACO-MKTA) algorithm is proposed, integrating observation, transmission, and charging into a unified planning framework. The algorithm employs a multi-knapsack-based task assignment strategy and local search enhanced ACO algorithm, significantly reducing the dimension of the original problem. The first simulation experiment validated the necessity of joint scheduling with energy constraint. After that, two comparative experiments were conducted to discuss the mechanism of local search and task assignment and then proved the efficiency of LSE-ACO-MKTA.