A memetic multi-agent collaboration search for space trajectory optimization

This paper presents the hybridisation of the fundamental heuristics underneath monotonic basin hopping within the general scheme of multi-agent collaborative search. The basic idea is that the local search performed by each individual agent in multi-agent collaborative search can be substituted with an iteration of basin hopping. Moreover, the local minima that are found during the search process are stored in an archive and at each iteration, the solution vector associated to each agent is extracted from the archive. The new hybrid algorithm is tested on some typical problems in space trajectory design and compared to monotonic basin hopping, a previous implementation of multi-agent collaborative search and to some standard evolutionary algorithms.