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Incorporating Risk in an Optimization Model of Reliability Engineering

Received: 21 November 2014     Accepted: 25 November 2014     Published: 27 December 2014
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Abstract

A non-repairable system is considered and the problem of finding its optimal preventive replacement time is revisited. In addition to minimizing the expected cost per unit time in a cycle, we also consider its variance as the measure of the risk of the optimal decision. A multi-objective optimization problem is then formulated where the two objective functions are the expectation and the variance. A sufficient condition is given for the existence of finite optimum in the case of the weighting method, where either the weight of the variance or the replacement costs are sufficiently small. In applying the ε - constraint method there is always finite optimum if the upper bound for the expectation is close to its minimal value.

Published in International Journal of Economic Behavior and Organization (Volume 3, Issue 2-1)

This article belongs to the Special Issue Recent Developments of Economic Theory and Its Applications

DOI 10.11648/j.ijebo.s.2015030201.11
Page(s) 1-4
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Certainty Equivalent, Reliability, Risk

References
[1] Beichelt, F (1993) A Unifying Treatment of Replacement Policies with Minimal Repair. Naval Research Logistics, 40: 51-67.
[2] Wang, H.Z. (2002) A Survey of Maintenance Policies of Deteriorating Systems. European Journal of Operational Research, 139 (3): 469-489.
[3] Nakagawa, T. (2006) Maintenance Theory and Reliability. Springer-Verlag, Berlin/Tokyo.
[4] Nakagawa, T. (2008) Advanced Reliability Models and Maintenance Policies. Springer-Verlag, Berlin/Tokyo.
[5] Elsayed, E.A. (2012) Reliability Engineering. John Wiley & Sons, Hoboken, New Jersey.
[6] Sargent, T.J. (1979) Macroeconomic Theory. Academic Press, New York.
[7] Szidarovszky, F., Gershon M.E., Duckstein, L. (1986) Techniques of Multiobjective Decision Making in Systems Management. Elsevier, Amsterdam.
Cite This Article
  • APA Style

    Akio Matsumoto, Ferenc Szidarovszky, Miklós Szidarovszky. (2014). Incorporating Risk in an Optimization Model of Reliability Engineering. International Journal of Economic Behavior and Organization, 3(2-1), 1-4. https://doi.org/10.11648/j.ijebo.s.2015030201.11

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    ACS Style

    Akio Matsumoto; Ferenc Szidarovszky; Miklós Szidarovszky. Incorporating Risk in an Optimization Model of Reliability Engineering. Int. J. Econ. Behav. Organ. 2014, 3(2-1), 1-4. doi: 10.11648/j.ijebo.s.2015030201.11

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    AMA Style

    Akio Matsumoto, Ferenc Szidarovszky, Miklós Szidarovszky. Incorporating Risk in an Optimization Model of Reliability Engineering. Int J Econ Behav Organ. 2014;3(2-1):1-4. doi: 10.11648/j.ijebo.s.2015030201.11

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  • @article{10.11648/j.ijebo.s.2015030201.11,
      author = {Akio Matsumoto and Ferenc Szidarovszky and Miklós Szidarovszky},
      title = {Incorporating Risk in an Optimization Model of Reliability Engineering},
      journal = {International Journal of Economic Behavior and Organization},
      volume = {3},
      number = {2-1},
      pages = {1-4},
      doi = {10.11648/j.ijebo.s.2015030201.11},
      url = {https://doi.org/10.11648/j.ijebo.s.2015030201.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.s.2015030201.11},
      abstract = {A non-repairable system is considered and the problem of finding its optimal preventive replacement time is revisited. In addition to minimizing the expected cost per unit time in a cycle, we also consider its variance as the measure of the risk of the optimal decision. A multi-objective optimization problem is then formulated where the two objective functions are the expectation and the variance. A sufficient condition is given for the existence of finite optimum in the case of the weighting method, where either the weight of the variance or the replacement costs are sufficiently small. In applying the ε - constraint method there is always finite optimum if the upper bound for the expectation is close to its minimal value.},
     year = {2014}
    }
    

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    T1  - Incorporating Risk in an Optimization Model of Reliability Engineering
    AU  - Akio Matsumoto
    AU  - Ferenc Szidarovszky
    AU  - Miklós Szidarovszky
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    DO  - 10.11648/j.ijebo.s.2015030201.11
    T2  - International Journal of Economic Behavior and Organization
    JF  - International Journal of Economic Behavior and Organization
    JO  - International Journal of Economic Behavior and Organization
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    UR  - https://doi.org/10.11648/j.ijebo.s.2015030201.11
    AB  - A non-repairable system is considered and the problem of finding its optimal preventive replacement time is revisited. In addition to minimizing the expected cost per unit time in a cycle, we also consider its variance as the measure of the risk of the optimal decision. A multi-objective optimization problem is then formulated where the two objective functions are the expectation and the variance. A sufficient condition is given for the existence of finite optimum in the case of the weighting method, where either the weight of the variance or the replacement costs are sufficiently small. In applying the ε - constraint method there is always finite optimum if the upper bound for the expectation is close to its minimal value.
    VL  - 3
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Author Information
  • Department of Economics, Chuo University, 742-1, Higashi-Nakano, Hachioji-shi, Tokyo, 192-0393, Japan

  • ReliaSoft Corporation, 1450 S. Eastside Loop, Tucson, Arizona 85710, USA

  • ReliaSoft Corporation, 1450 S. Eastside Loop, Tucson, Arizona 85710, USA

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