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Maximization problem of three tasks operation process subject to constraint of availability in semi-Markov reliability model

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Warianty tytułu
Konferencja
15th Summer Safety & Reliability Seminars - SSARS 2021, 5-12 September 2021, Ciechocinek, Poland
Języki publikacji
EN
Abstrakty
EN
Semi-Markov decision processes theory delivers the methods which allow to control the operation processes of the systems. The infinite duration semi-Markov decision processes are presented in the chapter. The gain maximization problem of three tasks operation processes subject to constraint of an availability of the semi-Markov reliability model is discussed. The problem is transformed on some linear programing maximization problem.
Bibliografia
  • Bernaciak, K. 2005. Multicriterial optimization of semi-Markov processes with discount. Advances in Safety and Reliability, 171-178.
  • Beutler, F. & Ross, K. 1986. Time-average optimal constrained semi-Markov decision processes. Advances in Applied Probability 18, 341-359.
  • Boussemart, M., Bicard, T. & Limnios, N. 2001. Markov decision processes with aconstraint on the average asymptotic failure rate. Methodology and Computing in Applied Probability 3(2), 199-214.
  • Boussemart, M. & Limnios, N. 2004. Markov decision processes with aconstraint on the average asymptotic failure rate. Communication in Statistics - Theory and Methods 33(7), 1689-1714.
  • Dong, Y, Teixeira, A.P. & Soares, C.G. 2020. Application of adaptive surrogate models in time-variant fatigue reliability assessment of welded joints with surface cracks. Reliability Engineering & System Safety 195, 106730.
  • Feinberg, E. 1994. Constrained semi-Markov decision processes with average rewards. Mathematical Methods of Operations Research 39, 257-288.
  • Gertsbakh, I.B. 1969. Models of preventive service. Sovetskoe radio, Moscow (in Russian).
  • Grabski, F. 2015. Semi-Markov Processes: Applications in System Reliability and Maintenance. Elsevier, Amsterdam - Boston - Heidelberg - London - New York - Oxford - Paris - San Diego - San Francisco - Sydney - Tokyo.
  • Grabski, F. 2018. Optimization problem of reliability subject to constraint of availability in semi-Markov models of operation. AIP Conference Proceedings 2116, London, 103-118.
  • Grabski, F. 2021. Maximization problem subject to constraint of availability in semi-Markov model of operation. Applied Modeling Techniques and Data Analysis 1 Computational Data Analysis Methods and Tools 7, 175-186.
  • Howard, R.A. 1960. Dynamic Programing and Markov Processes. MIT Press,Cambridge.
  • Howard, R.A. 1964. Research of semi-Markovian decision structures. Journal of Operations Research Society ofJapan 6, 163-199.
  • Howard, R.A. 1971. Dynamic probabilistic system. Semi-Markow and Decision Processes 2. Wiley, New York - London - Sydney - Toronto.
  • Jewell, W.S. 1963. Markov-renewal progra-mming. Operation Research 11, 938-971.
  • Korolyuk, V.S. & Turbin, A.F. 1976. Semi-Markov Processes and Their Applications.Naukova Dumka, Kiev (in Russian).
  • Li, H., Huang, H.Z. & Soares, C.G. 2020. Reliability analysis of a floating offshore wind turbine using Bayesian networks. Ocean Engineering 217,107827.
  • Limnios, N & Oprisan, G. 2001. Semi-Markov Processes and Reliability. Boston, Birkhauser.
  • Migawa, K. 2010. Semi-Markov model of the operation process included in an utilization subsystem of the transport system. TheArchives of AutomotiveEngineering 2, 87-97.
  • Mine, H. & Osaki, S. 1970. Markovian Decision Processes. AEPCI, New York.
  • Rong, H., Teixeira, A.P. & Soares, C.G. 2020. Data mining approach to shipping route characterization and anomaly detection based on AIS data. Ocean Engineering 198, 106936.
  • Silvestrov, D.C. 1980. Semi-Markov Processes with a Discrete State Space.Sovetskoe Radio, Moscow (in Russian).
  • Xu, S. & Soares, C.G. 2020. Experimental investigation on short-term fatigue damage of slack and hybrid mooring for wave energy converters. Ocean Engineering 195, 106618.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e6fa0a27-38d0-488b-aabb-75265738b845
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