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Multi-objective optimization for safety and reliability trade-off: Optimization and results processing

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  • Cristina Johansson
  • Johan Ölvander
  • Micael Derelöv

Abstract

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.

Suggested Citation

  • Cristina Johansson & Johan Ölvander & Micael Derelöv, 2018. "Multi-objective optimization for safety and reliability trade-off: Optimization and results processing," Journal of Risk and Reliability, , vol. 232(6), pages 661-676, December.
    • Handle: RePEc:sae:risrel:v:232:y:2018:i:6:p:661-676
    DOI: 10.1177/1748006X18757075
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    References listed on IDEAS

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    1. Ajit Kumar Verma & Ajit Srividya & Durga Rao Karanki, 2010. "Reliability and Safety Engineering," Springer Series in Reliability Engineering, Springer, number 978-1-84996-232-2, February.
    2. Limbourg, Philipp & Kochs, Hans-Dieter, 2008. "Multi-objective optimization of generalized reliability design problems using feature models—A concept for early design stages," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 815-828.
    3. Zio, Enrico & Podofillini, Luca, 2007. "Importance measures and genetic algorithms for designing a risk-informed optimally balanced system," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1435-1447.
    4. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    5. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, February.
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