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Complex system operation cost optimization

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The general model of a complex system changing its safety structure, its components safety parameters and its operation cost during the variable operation process and linear programming are applied to optimize the system operation process in order to get the system operation cost optimal values. The optimization problem allowing to find the optimal values of the transient probabilities of the complex system operation process at the particular operation states that minimize the system unconditional operation cost mean value in the safety states subset not worse than a critical system safety state under the assumption that the system conditional operation cost mean values in this safety state subset at the particular operation states are fixed is presented. Further, the procedure of finding the optimal values operation cost is presented and applied to the exemplary complex technical system.
Słowa kluczowe
Rocznik
Strony
13--18
Opis fizyczny
Bibliogr. 14 poz., tab.
Twórcy
  • Maritime University, Gdynia, Poland
  • Maritime University, Gdynia, Poland
Bibliografia
  • [1] Klabjan, D. & Adelman, D. (2006). Existence of optimal policies for semi-Markov decision processes using duality for infinite linear programming. Siam J Control Optim, 44, 6, 21042122.
  • [2] Kołowrocki, K. (2014). Reliability of large and complex systems. Elsevier.
  • [3] Kołowrocki, K. & Soszyńska, J. (2010). Reliability, availability and safety of complex technical systems: modeling – identification – prediction – optimization. J of Pol Saf and Reliab Assoc, Summer Safety and Reliability Seminars, 1, 1, 133-158.
  • [4] Kołowrocki, K. & Soszyńska-Budny, J. (2011). Reliability and Safety of Complex Technical Systems and Processes: Modeling-Identification Prediction-Optimization. Springer.
  • [5] Kołowrocki, K. & Soszyńska-Budny, J. (2012) Preliminary approach to safety analysis of critical infrastructures. J of Pol Saf and Reliab Assoc, Summer Safety and Reliability Seminars, 3, 7388.
  • [6] Kołowrocki, K. & Soszyńska-Budny, J. (2014). Prediction of Critical Infrastructures Safety. Proc. of The International Conference on Digital Technologies, Zilina, 141-149.
  • [7] Kuo, W. & Prasad, V. R. (2000). An annotated overview of system-reliability optimization. IEEE Trans on Reliab, 49, 2, 176-187.
  • [8] Kuo, W & Zuo, M. J. (2003). Optimal Reliability Modelling: Principles and Applications. Hoboken: John Wiley & Sons, Inc.
  • [9] Tang, H., Yin, B. G. & Xi, H. S. (2007). Error bounds of optimization algorithms for semiMarkov decision processes. Int J Syst Sc, 38, 9, 725-736.
  • [10] Vercellis, S. (2009). Data mining and optimization for decision making. John Wiley & Sons.
  • [11] Xue, J. (1985). On multi-state system analysis. IEEE Trans on Reliab, vol. 34, 329-337.
  • [12] Xue, J. & Yang, K. (1995). Dynamic reliability analysis of coherent multi-state systems. IEEE Trans on Reliab, 4, 44, 683-688.
  • [13] Xue, J. & Yang, K. (1995). Symmetric relations in multi-state systems. IEEE Trans on Reliab, 4, 44, 689-693.
  • [14] Yu, K., Koren, I. & Guo, Y. (1994). Generalised multistate monotone coherent systems. IEEE Trans on Reliab, 43, 242-250.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f6e37de2-75c4-4779-8223-a850b1fad4f7
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