Exact and heuristic approaches to detect failures in failed k-out-of-n systems

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Yavuz, Tonguç and Kundakçıoğlu, O. Erhun and Ünlüyurt, Tonguç (2019) Exact and heuristic approaches to detect failures in failed k-out-of-n systems. Computers and Operations Research . ISSN 0305-0548 (Print) 1873-765X (Online) Published Online First http://dx.doi.org/10.1016/j.cor.2019.07.010

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Official URL: http://dx.doi.org/10.1016/j.cor.2019.07.010


This paper considers a k-out-of-n system that has just failed. There is an associated cost of testing each component. In addition, we have apriori information regarding the probabilities that a certain set of components is the reason for the failure. The goal is to identify the subset of components that have caused the failure with the minimum expected cost. In this work, we provide exact and approximate policies that detects components’ states in a failed k-out-of-n system. We propose two integer programming (IP) formulations, two novel Markov decision process (MDP) based approaches, and two heuristic algorithms. We show the limitations of exact algorithms and effectiveness of proposed heuristic approaches on a set of randomly generated test instances. Despite longer CPU times, IP formulations are flexible in incorporating further restrictions such as test precedence relationships, if need be. Numerical results illustrate that dynamic programming for the proposed MDP model is the most effective exact method, solving up to 12 components within one hour. The heuristic algorithms’ performances are presented against exact approaches for small to medium sized instances and against a lower bound for larger instances.

Item Type:Article
Uncontrolled Keywords:k-out-of-n systems; Fault detection; Integer programing; Markov decision processes; Dynamic programing
Subjects:T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering > T57.6-57.97 Operations research. Systems analysis
ID Code:38016
Deposited By:Tonguç Ünlüyurt
Deposited On:29 Jul 2019 15:04
Last Modified:29 Jul 2019 15:04

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