Output details
12 - Aeronautical, Mechanical, Chemical and Manufacturing Engineering
University of Strathclyde
A hybrid multiagent approach for global trajectory optimization
First example of agent-based global optimisation combining local and global search through a hybridisation of agent-based search and deterministic branch & prune scheme with theoretical proof of convergence. The paper was recognised by CINVESTAV, one of the leading centres for evolutionary computation (schuetze@cs.cinvestav.mx), inspired developments by a group in the University of New South Wales (barkat@adfa.edu.au) and led to: an ESA Ariadna grant (Euro36k) on the global optimisation of space trajectories (leopold.summerer@esa.int), an invited key-note at the Wuhan State University of Geoscience, China, 2010, (Prof. Maocai Wang, cugwmc@gmail.com) and an invited tutorial session at EVOLVE2013, Leiden, 2013 (emmerich@liacs.nl).
