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Strategic maintenance planning by fuzzy AHP and Markov Decision Processes

Authors:

Sahar Tahvili, Jonas Österberg , Sergei Silvestrov

Research group:

Software Testing Laboratory

Publication Type:

Conference/Workshop Paper

Venue:

16th Conference of the Applied Stochastic Models and Data Analysis International Society

Abstract

The work of engineering and business professionals includes making a series of decisions and optimizations. Real world decision making problems faced by decision makers (DM) involve multiple, usually con icting, criteria. These multicriteria decision making problems (MCDM) are usually complicated and large in scale. In strategic Maintenance planning, choices are made on where to focus time and e ort, where to spend money. We consider a framework for strategic maintenance planning in a modern maintenance driven organization. Our focus is on a multi-stage framework in which the planning is divided into two stages, identifying an optimal set of possible actions and nding the optimal decision policy for these actions for each point in time as a function of the stochastically evolving system state. To this respect we consider the MCDM method of AHP (Analytical hierarchical programming) in a fuzzy environment, and Markov decision processes (MDP).

Bibtex

@inproceedings{Tahvili4147,
author = {Sahar Tahvili and Jonas {\"O}sterberg and Sergei Silvestrov},
title = {Strategic maintenance planning by fuzzy AHP and Markov Decision Processes},
year = {2015},
booktitle = {16th Conference of the Applied Stochastic Models and Data Analysis International Society},
url = {http://www.es.mdu.se/publications/4147-}
}