Marilena Di Carlo

Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart

In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.

Optimal trajectory planning for multiple asteroid tour mission by means of an incremental bio-inspired tree search algorithm

In this paper, a combinatorial optimisation algorithm inspired by the Physarum Polycephalum mould is presented and applied to the optimal trajectory planning of a multiple asteroid tour mission. The Automatic Incremental Decision Making And Planning (AIDMAP) algorithm is capable of solving complex discrete decision making problems with the use of the growth and exploration of the decision network. The stochastic AIDMAP algorithm has been tested on two discrete astrodynamic decision making problems of increased complexity and compared in terms of accuracy and computational cost to its deterministic counterpart. The results obtained for a mission to the Atira asteroids and to the Main Asteroid Belt show that this non-deterministic algorithm is a good alternative to the use of traditional deterministic combinatorial solvers, as the computational cost scales better with the complexity of the problem.

Human exploration of cis-lunar space via assets tele-operated from EML2 (HECATE)

This paper presents the preliminary design of the international space mission HECATE (Human Exploration of Cis-lunar space via Assets Tele-operated from EML-2), aimed at exploring the far side of the Moon via tele-robotic activities during the 2020s. The exploration is realized by astronauts from HOPE (Human Orbiting Protected Environment), a space habitat in a halo orbit around the Earth-Moon Lagrange Point 2, a critical staging location for future robotic and human deep space missions. Inside the habitat, astronauts have access to tele-robotic hardware and instruments, used to tele-operate rovers and scientific equipment on the surface of the Moon. Plans to resupply and maintain HOPE for future missions, using a solar electric tug, are given. Ultimately, HOPE represents an energetically favorable intermediate locations for missions to Mars, Near-Earth Asteroids, and beyond.

Multi-objective optimisation of constellation deployment using low-thrust propulsion

This work presents an analysis of the deployment of future constellations using a com-bination of low-thrust propulsion and natural dynamics. Different strategies to realise the transfer from the launcher injection orbit to the constellation operational orbit are investigated. The deployment of the constellation is formulated as a multi-objective optimisation problem that aims at minimising the maximum transfer ΔV, the launch cost and maximise at the same time the pay-off given by the service provided by the constellation. The paperwill consider the case of a typical constellation with 27 satellites in Medium Earth Orbit and the use of only two launchers, one of which can carry a single satellite. It will be demonstrated that some strategies and deployment sequences are dominant and provide the best trade-off between peak transfer ΔV and monetary pay-off.