• Journal of Applied Reliability
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• v.5 no.3
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• pp.373-379
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• 2005

In many cases, it is more practical and economical to repair a system than to replace the whole system or to perform a complete overhaul when the system fails. Two basic replacement policies were proposed by Barlow and Hunter(1960) and Morimura (1970), in which the minimal repair times are identically distributed. But, as Lam(1988) pointed out, in many cases of deteriorating system, in view of ageing and cumulative wear, the repair time will tend to be longer and longer. In this note, the two basic replacement policies are considered for a repairable system with linearly increasing repair times. Optimal policies, which maximize the steady state availability of the system, are obtained for the Weibull failure rate case.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1239-1247
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• 2010

In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The intensity function used Gompertz, Preto and Log-logstic pattern which has the efficient various property. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.1-9
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• 2008

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, because of the possibility of introducing new faults when correcting or modifying the software, infinite failure non-homogeneous Poisson process models presented and propose an optimal release policies of the life distribution applied log-logistic distribution which can capture the increasing! decreasing nature of the failure occurrence rate per fault. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, make out estimating software optimal release time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.8
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• pp.1903-1910
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• 2009

In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.1-9
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• 2009

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, because of the possibility of introducing new faults when correcting or modifying the software, infinite failure non-homogeneous Poisson process models presented and propose an optimal release policies of the life distribution applied fixed shape parameter distribution which can capture the increasing/decreasing nature of the failure occurrence rate per fault. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, make out estimating software optimal release time

• Journal of the Korean Mathematical Society
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• v.44 no.1
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• pp.139-150
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• 2007

We investigate an optimal portfolio selection problem with transaction costs when an illiquid asset pays cash dividends and there are constraints on the illiquid asset holding. We provide closed form solutions for the problem, and by using these solutions we illustrate interesting features of optimal policies.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.107-117
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• 2002

In this paper we present the optimal replacement policies following the expiration of combination warranty. We consider two types of combination warranty policies: renewing warranty and non-renewing warranty. The criterion used to determine the optimal replacement period is the expected cost rate per unit time from the user'perspective. The optimal maintenance period following the expiration of combination warranty is obtained. Some numerical examples are presented for illustrative purpose.

• East Asian mathematical journal
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• v.38 no.3
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• pp.277-292
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• 2022

This study investigates the convergence of the optimal consumption and investment policies in a binomial-tree model to those in the continuous-time model of Merton (1969). We provide the convergence in explicit form and show that the convergence rate is of order ∆t, which is the length of time between consecutive time points. We also show by numerical solutions with realistic parameter values that the optimal policies in the binomial-tree model do not differ significantly from those in the continuous-time model for long-term portfolio management with a horizon over 30 years if rebalancing is done every 6 months.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.125-132
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• 2010

Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used exponential and non-exponential family which has various intensity. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.