A Mixed Integer Linear Programming Model for Multi-Satellite Scheduling

TL;DR

This paper presents a mixed integer linear programming model for optimizing multi-satellite observation scheduling, effectively handling resource constraints and interdependencies to improve mission planning accuracy.

Contribution

The paper introduces a novel MILP model that explicitly accounts for conflict indicators and feasible time intervals in satellite scheduling problems.

Findings

Model effectively finds optimal or near-optimal solutions.

Applicable to real-world satellite scheduling scenarios.

Demonstrates computational efficiency on various instances.

Abstract

We address the multi-satellite scheduling problem with limited observation capacities that arises from the need to observe a set of targets on the Earth's surface using imaging resources installed on a set of satellites. We define and analyze the conflict indicators of all available visible time windows of missions, as well as the feasible time intervals of resources. The problem is then formulated as a mixed integer linear programming model, in which constraints are derived from a careful analysis of the interdependency between feasible time intervals that are eligible for observations. We apply the proposed model to several different problem instances that reflect real-world situations. The computational results verify that our approach is effective for obtaining optimum solutions or solutions with a very good quality.