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Robust mission design through evidence theory and multiagent collaborative search.

Massimiliano Vasile1

  • 1Dipartimento di Ingegneria Aerospaziale, Politecnico di Milano, Milan, Italy. m.vasile@eng.gla.ac.uk

Annals of the New York Academy of Sciences
|March 3, 2006
PubMed
Summary

This study introduces a novel approach to space mission design by incorporating uncertainties. A new multiobjective optimization algorithm enhances mission reliability and goal achievement, ensuring successful space exploration.

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Area of Science:

  • Aerospace Engineering
  • Mission Design
  • Reliability Engineering

Background:

  • Space mission design often faces uncertainties in key parameters.
  • Ensuring mission success requires robust reliability analysis.
  • Existing methods may not fully address complex uncertainties.

Purpose of the Study:

  • To develop a preliminary design methodology for space missions under uncertainty.
  • To formulate reliable design as a multiobjective optimization problem.
  • To maximize mission goal achievement and constraint satisfaction reliability.

Main Methods:

  • Uncertainties in design parameters are modeled using evidence theory.
  • A multiobjective optimization problem is formulated to balance competing objectives.

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  • A novel agent-based collaborative algorithm is employed to find reliable solutions.

    • Main Results:

    • The methodology effectively handles uncertainties in preliminary space mission design.
    • The proposed algorithm identifies a set of highly reliable solutions.
    • Demonstrated applicability through two typical mission analysis problems.

    Conclusions:

    • The presented approach provides a robust framework for reliable space mission design.
    • Evidence theory and multiobjective optimization offer powerful tools for managing design uncertainties.
    • The novel agent-based algorithm shows promise for solving complex reliability-focused optimization problems.