MHACO : a multi-objective hypervolume-based ant colony optimizer for apace trajectory optimization

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Acciarini, Giacomo and Izzo, Dario and Mooij, Erwin (2020) MHACO : a multi-objective hypervolume-based ant colony optimizer for apace trajectory optimization. In: IEEE World Congress on Computational Intelligence (WCCI) 2020, 2020-07-19 - 2020-07-24, Online.

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Abstract

In this paper, we combine the concepts of hypervolume, ant colony optimization and nondominated sorting to develop a novel multi-objective ant colony optimizer for global space trajectory optimization. In particular, this algorithm is first tested on three space trajectory bi-objective test problems: an Earth-Mars transfer, an Earth-Venus transfer and a bi-objective version of the Jupiter Icy Moons Explorer mission (the first large-class mission of the European Space Agency’s Cosmic Vision 2015-2025 programme). Finally, the algorithm is applied to a four-objectives low-thrust problem that describes the journey of a solar sail towards a polar orbit around the Sun. The results on both the test cases and the more complex problem are reported by comparing the novel algorithm performances with those of two popular multi-objective optimizers (i.e., a nondominated sorting genetic algorithm and a multi-objective evolutionary algorithm with decomposition) in terms of hypervolume metric. The numerical results of this study show that the multi-objective hypervolume-based ant colony optimization algorithm is not only competitive with the standard multi-objective algorithms when applied to the space trajectory test cases, but it can also provide better Pareto fronts in terms of hypervolume values when applied to the complex solar sailing mission.

  • Item type:Conference or Workshop Item(Paper)
    ID code:73899
    Dates:
    Date
    Event
    20 July 2020
    Published
    15 March 2020
    Accepted
    Notes:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Motor vehicles. Aeronautics. Astronautics
    Technology > Mechanical engineering and machinery
    Department:Faculty of Engineering > Mechanical and Aerospace Engineering
    Depositing user: Pure Administrator
    Date deposited:17 Sep 2020 10:45
    Last modified:11 Nov 2024 17:02
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/73899
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