A Heuristic Policy for Maintaining Multiple Multi-State Systems - Zhang, Mimi (My University, 2020)
This work is concerned with the optimal allocation of limited maintenance resources among a collection of competing multi-state systems, and the dynamic of each multi-state system is modelled by a Markov chain. Determining the optimal dynamic maintenance policy is prohibitively difficult, and hence we propose a heuristic dynamic maintenance policy in which maintenance resources are allocated to systems with higher importance. The importance mea-sure is well justified by the idea of subsidy, yet the computation is expensive. Hence, we further propose two modifications of the importance measure, resulting in two modified heuristic policies. The performance of the two modified heuristics is evaluated in a systematic computational study, showing exceptional competence.
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Keywords: Approximate linear programming; Expected discounted reward; Partially observable Markov decision process