A simple suboptimal algorithm for system maintance under partial observability

DOI10.1023/A:1018949723461zbMath0970.90023OpenAlexW176192368MaRDI QIDQ1819267

Zilla Sinuany-Stern, Lea Friedman, Israel David

Publication date: 11 January 2000

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1018949723461

zbMATH Keywords

dynamic programmingmachine replacementsuboptimal algorithmspartially observed Markov decision processBasyesian programmingreliability/maintenance

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Reliability, availability, maintenance, inspection in operations research (90B25) Markov and semi-Markov decision processes (90C40) Applications of renewal theory (reliability, demand theory, etc.) (60K10)

Related Items (2)

Foundations of operations research: from linear programming to data envelopment analysis ⋮ Modelling of hydrological persistence for hidden state Markov decision processes

Cites Work

• Application of Jensen's inequality to adaptive suboptimal design
• Dynamic programming and stochastic control
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• An efficient heuristic for a partially observable Markov decision process of machine replacement
• A survey of algorithmic methods for partially observed Markov decision processes
• A Partially Observable Markov Decision Process with Lagged Information
• A Partially Observable Model of Decision Making by Fishermen
• Structural Results for Partially Observable Markov Decision Processes
• State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms
• Computationally Feasible Bounds for Partially Observed Markov Decision Processes
• A Markov Quality Control Process Subject to Partial Observation
• Optimal control-limit strategies for a partially observed replacement problem†
• Finite-Memory Suboptimal Design for Partially Observed Markov Decision Processes
• A Two-State Partially Observable Markov Decision Process with Uniformly Distributed Observations

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