A multidirectional Physarum solver for the automated design of space trajectories
Masi, Luca and Vasile, Massimiliano; (2014) A multidirectional Physarum solver for the automated design of space trajectories. In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers Inc., GBR, pp. 2992-2999. ISBN 978-1-4799-6626-4
|
Text (Masi-Vasile-CEC-2014-A-multidirectional-physarum-solver-automated-design-space-trajectories-Jul-2014)
Masi_Vasile_CEC_2014_A_multidirectional_physarum_solver_automated_design_space_trajectories_Jul_2014.pdf Accepted Author Manuscript Download (308kB)| Preview |
Abstract
This paper proposes a bio-inspired algorithm to automatically generate optimal multi-gravity assist trajectories.The multi-gravity assist problem has some analogies with the better known Traveling Salesman Problem and can be addressed with similar strategies. An algorithm drawing inspiration from the Physarum slime mould is proposed to grow and explore a tree of decisions that corresponds to the possible sequences of transfers from one planet to another. Some examples show that the proposed bio-inspired algorithm can produce solutions that are better than the ones generated by humans or with Hidden Genes Genetic Algorithms.
Creators(s): |
Masi, Luca ![]() ![]() | Item type: | Book Section |
---|---|
ID code: | 53956 |
Notes: | Date of Acceptance: 15/03/2014 |
Keywords: | aerospace control, Physarum slime mould, hidden genes genetic algorithms, multigravity assist problem, Mechanical engineering and machinery, Artificial Intelligence, Computational Theory and Mathematics, Theoretical Computer Science |
Subjects: | Technology > Mechanical engineering and machinery |
Department: | Faculty of Engineering > Mechanical and Aerospace Engineering Technology and Innovation Centre > Advanced Engineering and Manufacturing University of Strathclyde > University of Strathclyde |
Depositing user: | Pure Administrator |
Date deposited: | 11 Aug 2015 13:32 |
Last modified: | 20 Jan 2021 15:39 |
Related URLs: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/53956 |
Export data: |