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

Name: Exact and heuristic approaches to detect failures in failed k-out-of-n systems
Author: Yavuz, Tonguç, Kundakcıoğlu, Ömer Erhun, Ünlüyurt, T.

İsim	Exact and heuristic approaches to detect failures in failed k-out-of-n systems
Yazar	Yavuz, Tonguç, Kundakcıoğlu, Ömer Erhun, Ünlüyurt, T.
Basım Tarihi:	2019-12
Basım Yeri	- Elsevier
Konu	K-out-of-n systems, Fault detection, Integer programming, Markov decision processes, Dynamic programming
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0305-0548
Kayıt Numarası	ae1c1e48-0d2c-4014-aad8-923b27677af4
Lokasyon	Industrial Engineering
Tarih	2019-12
Örnek Metin	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.
DOI	10.1016/j.cor.2019.07.010
Cilt	112

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

Yazar Yavuz, Tonguç, Kundakcıoğlu, Ömer Erhun, Ünlüyurt, T.

Basım Tarihi 2019-12

Basım Yeri - Elsevier

Konu K-out-of-n systems, Fault detection, Integer programming, Markov decision processes, Dynamic programming

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0305-0548

Kayıt Numarası ae1c1e48-0d2c-4014-aad8-923b27677af4

Lokasyon Industrial Engineering

Tarih 2019-12

Örnek Metin 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.

DOI 10.1016/j.cor.2019.07.010

Cilt 112