Optimal replacement policies with minimal repair and age-dependent costs

Chen, Mingchih; Feldman, Richard M.

doi:10.1016/0377-2217(95)00320-7

Cited by 68 publications

(24 citation statements)

References 7 publications

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“…for the value iteration method. This long execution time is also due to the computation of c(s, a), which requires to solve the service selection optimization problem (see (8)). Therefore, the reduced computational cost of the 1-step horizon policy makes it amenable to take online admission control decisions.…”

Section: Resultsmentioning

confidence: 99%

“…A considerable number of research efforts have focused on the application of MDP-based models and stochastic programming to SOA systems and, more generally, to software systems [2,3,5,[8][9][10]12,14]. Some of these works have proposed self-healing approaches in order to support the reconfiguration of running services, e.g., [3,8], considering also proactive solutions for SOA systems [12].…”

Section: Introductionmentioning

confidence: 99%

“…Some of these works have proposed self-healing approaches in order to support the reconfiguration of running services, e.g., [3,8], considering also proactive solutions for SOA systems [12]. Some recent approaches [9,10,14] have used MDPs to model service composition with the aim to create automatically an abstract workflow of the service composition that satisfies functional and non-functional requirements, and also to allow the composite service to adapt dynamically to a varying environment [14].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Admission Control for a QoS-Aware Service-Oriented System

Abundo

Cardellini

Presti

2011

Towards a Service-Based Internet

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Abstract. In the service computing paradigm, a service broker can build new applications by composing network-accessible services offered by loosely coupled independent providers. In this paper, we address the admission control problem for a a service broker which offers to prospective users a composite service with a range of different Quality of Service (QoS) classes. We formulate the problem as a Markov Decision Process (MDP) problem with the goal of maximizing the broker revenue while guaranteeing non-functional QoS requirements to its already admitted users. To assess the effectiveness of the MDP-based admission control, we present experimental results where we compare the optimal decisions obtained by the analytical solution of the MDP with other policies.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Admission Control for a QoS-Aware Service-Oriented System

Abundo

Cardellini

Presti

2011

Towards a Service-Based Internet

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“…Under the Markov formulation, the sojourn time in each state is restricted to be exponentially distributed (Sherif and Smith 1981;Lam and Yeh 1994;Chiang and Yuan 2001;Yeh 1997). To have a better description of the empirical evidence, semi-Markov process have been employed to model multistate deteriorating systems (Chen and Trivedi 2005;Moustafa et al 2004;Yeh 1997;Chen and Feldman 1997) by allowing the sojourn time distribution to be non-exponential. In our previous work (Moustafa et al 2004), we proposed a maintenance model for a multi-state semi-Markov one-unit deteriorating system.…”

Section: Introductionmentioning

confidence: 99%

A semi-Markov decision algorithm for the optimal maintenance of a multistage deteriorating two-unit standby system

Maksoud

Moustafa

2008

Oper Res Int J

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The semi-Markov decision model is a powerful tool in analyzing sequential decision processes with random decision epochs for a multi-state deteriorating system subject to aging and fatal shocks. In this paper, we propose a model for a two-unit standby system where a cold standby unit is attached to an operating (active) one. For this model, the active unit goes through a finite number of states of successive degradation preceding the failure, while the other one is in cold standby state. At each deterioration state of the active unit, two types of maintenance are considered, minimal and major, depending on the degrading level. The minimal maintenance aims to improve the degradation of the unit by recovering it to the previous degradation stage. The maximum allowable number of minimal maintenances for all states of the active unit must not exceed a certain limit. On the other hand, the major maintenance is necessary when the active unit fails. Once this maintenance is completed, the unit is restored to as good as new. To make the system operate more time without any interruption, the standby unit can be switched online until the active unit finishes its minimal or major maintenance. The switch between the two units is perfect and switchover is instantaneous. After using the standby unit, it is serviced or overhauled to maintain it in as good as new state. We use an iterative numerical approach, based on the policy iteration method, to drive the optimal state-dependent maintenance policy that minimizes the long-run expected cost rate of the system. Finally,

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“…Traditional maintenance actions consist of repair and replacement activities (Chen and Feldman, 1997;Wang, 2002). However, in addition to these two commonly accepted maintenance actions, there are many other actions that can be used as a maintenance response to combat machine degradation and failure.…”

Section: Introductionmentioning

confidence: 99%

Maintenance scheduling for a manufacturing system of machines with adjustable throughput

Yang

Djurdjanović

2007

IIE Transactions

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This paper considers the problem of analyzing and optimizing joint schedules of maintenance and throughput adjustment operations in manufacturing systems. The purpose of joint scheduling of maintenance and throughput changing operations is to maximize the cost benefits of maintenance operations in manufacturing systems in which some or all of the machines can execute their function under different process settings, resulting in different machine and system throughputs. Such a capability enables one to strategically slow down more degraded machines or accelerate freshly maintained machines so that production targets can be met and maintenance operations can be offset to times when they are less intrusive on the manufacturing process. A Monte-Carlo-simulation-based method is proposed for the evaluation of cost effectiveness of any schedule of maintenance and throughput changing operations, and a geneticalgorithm-based method is proposed to enable searching for schedules that would maximize the cost benefits of these operations. A matrix chromosome representation of the joint schedules of maintenance and throughput adjustment operations is introduced and several mechanisms of chromosome evolution and selection are proposed and analyzed in numerical simulations of such manufacturing systems. Results indicate a good ability for the newly proposed methods to achieve a tradeoff between cost benefits of production and losses due to maintenance operations through strategic allocation of maintenance and throughput changing actions.

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Optimal replacement policies with minimal repair and age-dependent costs

Cited by 68 publications

References 7 publications

Optimal Admission Control for a QoS-Aware Service-Oriented System

Optimal Admission Control for a QoS-Aware Service-Oriented System

A semi-Markov decision algorithm for the optimal maintenance of a multistage deteriorating two-unit standby system

Maintenance scheduling for a manufacturing system of machines with adjustable throughput

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