The purpose of our research is two-fold: first, to propose, analyse and develop techniques aimed on building efficient plans (with a scope that can range from years to a day) fulfilling all the constraints of the problem that can be predicted; and second, to define and implement processes that adapt the ideal plans reacting dynamically to unexpected situations in a short period of time (in the order of a few seconds).

The first research line is framed in the field of global search devoted to automated planning and scheduling for constraint-based problems. Particularly, we mainly focus on scheduler systems based on Evolutionary Algorithms (e.g., Genetic Algorithms) and Swarm Intelligence (e.g., Particle Swarm optimization), which are Artificial Intelligence techniques that emulate natural evolution by means of combining potential solutions using selection, combination and mutation operators, or that emulate the behavior of descentralized and self-organized systems in the nature. The goal of these optimization algorithms is to efficiently explore a large amount of potential solutions in order to find near-optimal solutions that result in efficient observation plans. A solution is considered near-optimal (or efficient) when it fulfils all problem constraints and it highly optimises the objectives defined by the problem (i.e., maximisation of the time observing objects, minimization of idle time, maximisation of completed proposals, etc.). In this sense, we have demonstrated that Multi-Objective Evolutionary and Particle Swarm algorithms are promising approaches to addressing complex and diverse problems of multi-objective optimization, and we continue exploring different methodologies.

The second research line is focused on defining dispatcher algorithms based on astronomical heuristics that repair the ideal plans avoiding intensive calculations in order to provide a response in a few seconds. This step requires a great understanding of the problem where the process is being applied in order to define rules that model the reaction that scientists/engineers/operators expect in particular situations, without leaving aside the optimization obtained by the scheduler system.

In addition, ICE-CSIC is one of the institutions developing STARS, a software library that provides tools for the scheduling of astronomical observations and tasks. Users can also access the graphical interface to visualise schedules.