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Reliability-Based Optimization Using Differential Evolution and Inverse Reliability Analysis for Engineering System Design

Author

Listed:
  • Fran S. Lobato

    (Federal University of Uberlândia)

  • Matheus S. Gonçalves

    (Federal University of Santa Catarina)

  • Bárbara Jahn

    (Federal University of Uberlândia)

  • Aldemir Ap. Cavalini

    (Federal University of Uberlândia)

  • Valder Steffen

    (Federal University of Uberlândia)

Abstract

In this contribution, a new methodology based on a double-loop iteration process is proposed for the treatment of uncertainties in engineering system design. The inner optimization loop is used to find the solution associated with the highest probability value (inverse reliability analysis), and the outer loop is the regular optimization loop used to solve the considered reliability problem through differential evolution and multi-objective optimization differential evolution algorithms. The proposed methodology is applied to mathematical functions and to the design of classical engineering systems according to both mono- and multi-objective contexts. The obtained results are compared with those obtained by classical approaches and demonstrate that the proposed strategy represents an interesting alternative to reliability design of engineering systems.

Suggested Citation

  • Fran S. Lobato & Matheus S. Gonçalves & Bárbara Jahn & Aldemir Ap. Cavalini & Valder Steffen, 2017. "Reliability-Based Optimization Using Differential Evolution and Inverse Reliability Analysis for Engineering System Design," Journal of Optimization Theory and Applications, Springer, vol. 174(3), pages 894-926, September.
    • Handle: RePEc:spr:joptap:v:174:y:2017:i:3:d:10.1007_s10957-017-1063-x
    DOI: 10.1007/s10957-017-1063-x
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    Cited by:

    1. Van Huynh, Thu & Tangaramvong, Sawekchai & Do, Bach & Gao, Wei & Limkatanyu, Suchart, 2023. "Sequential most probable point update combining Gaussian process and comprehensive learning PSO for structural reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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