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EOSpython Version 0.0.11: A Framework for Scenario Generation and a Solution System for the Agile Earth Observation Satellite Scheduling Problem

Alex Elkjær Vasegaard, Andreas Kühne Larsen

Abstract

EOSpython is a PyPI published Python package that encompass everything within a centralized earth observation satellite scheduling system in terms of customer database setup, scenario generation, pre-processing, problem setup, scheduling solution approach, decision maker preference integration, and visualization. The package is tailored to easily configure internal parameters and contribute with other solution approaches.

EOSpython Version 0.0.11: A Framework for Scenario Generation and a Solution System for the Agile Earth Observation Satellite Scheduling Problem

Abstract

EOSpython is a PyPI published Python package that encompass everything within a centralized earth observation satellite scheduling system in terms of customer database setup, scenario generation, pre-processing, problem setup, scheduling solution approach, decision maker preference integration, and visualization. The package is tailored to easily configure internal parameters and contribute with other solution approaches.

Paper Structure

This paper contains 12 sections, 1 equation, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. Scenario Generation
  3. Customer Database Generation
  4. Satellite Information and TLE Data
  5. Scenario Realization and Map Generation
  6. Linear Programming Problem (LPP) Setup
  7. Problem Formulation
  8. Solution Approach
  9. Example on Usage
  10. How to contribute and collaborate
  11. Future work
  12. Conclusion

Figures (2)

  • Figure 1: The interactive html output of the Visualize() function, displaying a solved scenario of the SIASP vasegaard2022determining. The scenario is the example from Section 5.
  • Figure 2: The functional overview of the EOSpython package framework.