Benchmarking different global optimisation techniques for preliminary space trajectory design

In this paper we describe a number of global optimisation problems connected to spacecraft trajectory design. Each problem is coded in the form of a blackbox objective function accepting, as inputs, the decision vector and returning the objective function and the constraint evaluation. The code is made available on line as a challenge to the community to develop performing algorithms able to solve each of the problems proposed in an efficient manners. All the problems proposed draw inspiration from real trajectory problems, ranging from Cassini to Rossetta to Messenger to possible future missions. As a start we also report the results coming from applying standard global optimisation algorithm to each of the problem. We consider Differential Evolution, Particle Swarm Optimisation, Genetic Algorithm, Adaptive Simulated Annealing and GLOBAL. As all these standard implementations seem to fail to solve more complex problems, we conclude the paper suggesting a cooperative approach between the different algorithm showing performance improvements.