# Constraint programming for planning test campaigns of communications satellites

## TL;DR

This paper presents a constraint programming approach to optimize the planning of satellite payload test campaigns by minimizing configurations and equipment switches, ensuring thermal stability and reducing campaign duration.

## Contribution

It introduces novel constraint models and search strategies for the combined packing and sequencing sub-problems in satellite test planning.

## Key findings

- Models improve lower bounds for configuration packing.
- Enhanced propagation algorithms for equipment switch constraints.
- Experimental results on real and random instances validate the approach.

## Abstract

The payload of communications satellites must go through a series of tests to assert their ability to survive in space. Each test involves some equipment of the payload to be active, which has an impact on the temperature of the payload. Sequencing these tests in a way that ensures the thermal stability of the payload and minimizes the overall duration of the test campaign is a very important objective for satellite manufacturers. The problem can be decomposed in two sub-problems corresponding to two objectives: First, the number of distinct configurations necessary to run the tests must be minimized. This can be modeled as packing the tests into configurations, and we introduce a set of implied constraints to improve the lower bound of the model. Second, tests must be sequenced so that the number of times an equipment unit has to be switched on or off is minimized. We model this aspect using the constraint Switch, where a buffer with limited capacity represents the currently active equipment units, and we introduce an improvement of the propagation algorithm for this constraint. We then introduce a search strategy in which we sequentially solve the sub-problems (packing and sequencing). Experiments conducted on real and random instances show the respective interest of our contributions.