Journal ArticleDOI
Road maintenance optimization through a discrete-time semi-Markov decision process
Xuan Zhang,Hui Gao +1 more
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TLDR
These linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets.About:
This article is published in Reliability Engineering & System Safety.The article was published on 2012-07-01. It has received 50 citations till now. The article focuses on the topics: Partially observable Markov decision process & Markov process.read more
Citations
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Journal ArticleDOI
A Markov-Based Road Maintenance Optimization Model Considering User Costs
Hui Gao,Xuan Zhang +1 more
TL;DR: This article describes how user costs of different maintenance actions need to be assessed in road maintenance as well as the maintenance costs and develops a multiobjective Markov-based model to minimize both maintenance cost and user cost subject to a number of constraints.
Journal ArticleDOI
Maintenance scheduling of geographically distributed assets with prognostics information
TL;DR: A methodology to schedule the maintenance of geographically distributed assets using their prognostic information and a Genetic Algorithm based solution incorporating the daily work duration of the maintenance team is presented in the paper.
Journal ArticleDOI
The reliability of technological systems with high energy efficiency in residential buildings
TL;DR: In this paper, the authors highlight the importance of the reliability parameters because of some changes that occurred in modern technology; as for example the necessity of more sophisticated equipments or plants transformed from an auxiliary service to being an actual part of the systems they were originally intended for.
Journal ArticleDOI
Optimization in Decision Making in Infrastructure Asset Management: A Review
TL;DR: According to the literature review, this paper confirms optimization can effectively assist DM in IAM and a wide range of optimization methods are applicable to assist a variety of DM problems.
Journal ArticleDOI
Modeling and analysis for multi-state systems with discrete-time Markov regime-switching
TL;DR: The main focus of this paper is on the development of reliability measures for a repairable multi-state system which operates under dynamic regimes under the discrete-time hypothesis and some novel reliability indices are introduced.
References
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Book
Markov Decision Processes: Discrete Stochastic Dynamic Programming
TL;DR: Puterman as discussed by the authors provides a uniquely up-to-date, unified, and rigorous treatment of the theoretical, computational, and applied research on Markov decision process models, focusing primarily on infinite horizon discrete time models and models with discrete time spaces while also examining models with arbitrary state spaces, finite horizon models, and continuous time discrete state models.
Journal ArticleDOI
Introduction to Probability Models.
TL;DR: There is a comprehensive introduction to the applied models of probability that stresses intuition, and both professionals, researchers, and the interested reader will agree that this is the most solid and widely used book for probability theory.
Book
Bayesian inference in statistical analysis
George E. P. Box,George C. Tiao +1 more
TL;DR: In this article, the effect of non-normality on inference about a population mean with generalizations was investigated. But the authors focused on the effect on the mean with information from more than one source.
Journal ArticleDOI
Bayesian Inference in Statistical Analysis
Book
Probability Concepts in Engineering Planning and Design
TL;DR: This research attacked the mode confusion problem by developing a modeling framework called “model schizophrenia” to estimate the posterior probability of various modeled errors.
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Optimal replacement of a system according toa semi-Markov decision process in a semi-Markov environment
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