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Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis Using a Phase Methodology

Akram Khaleghei, Michael Jong Kim

2021Operations Research15 citationsDOI

Abstract

In “Optimal Control of Partially Observable Semi-Markovian Failing Systems: An Analysis using a Phase Methodology,” Khaleghei and Kim study a maintenance control problem a as partially observable semi-Markov decision process (POSMDP), a problem class that is typically computationally intractable and not amenable to structural analysis. The authors develop a new approach based on a phase methodology where the idea is to view the intractable POSMDP as the limiting problem of a sequence of tractable POMDPs. They show that the optimal control policy can be represented as a control limit policy which monitors the estimated conditional reliability at each decision epoch, and, by exploiting this structure, an efficient computational approach to solve for the optimal control limit and corresponding optimal value is developed.

Topics & Concepts

ObservableMarkov decision processLimit (mathematics)Computer scienceOptimal controlMathematical optimizationMarkov processPartially observable Markov decision processSequence (biology)Control (management)Reliability (semiconductor)Class (philosophy)Markov chainControl limitsPhase (matter)Process (computing)MathematicsArtificial intelligenceStatisticsMathematical analysisOrganic chemistryQuantum mechanicsControl chartBiologyPower (physics)Machine learningChemistryPhysicsGeneticsOperating systemReliability and Maintenance OptimizationRisk and Safety AnalysisProbabilistic and Robust Engineering Design
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