• Proceedings of the Korean Reliability Society Conference
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• 2002.06a
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• pp.273-273
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• 2002

In this paper, we investigate a software release policy with software reliability growth factor during the warranty period by assuming that the software reliability growth is assumed to occur after the testing phase with probability p and the software reliability growth is not assumed to occur after the testing phase with probability 1-p. The optimal release policy to minimize the expected total software cost is discussed. Numerical examples are shown to illustrate the results of the optimal policy. And we consider a Bayesian decision theoretic approach to determine an optimal software release policy. This approach enables us to update our uncertainty when determining optimal software release time, When the failure time is Weibull distribution with uncertain parameters, a bayesian approach is established. Finally, numerical examples are presented for illustrative propose.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.673-682
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• 2005

In this paper, we generalize the software reliability growth model by assuming that the testing cost and maintenance cost are random and adopt the Bayesian approach to determine the optimal software release time. Numerical examples are provided to illustrate the Bayesian method for certain parametric models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.1-6
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• 1990

This paper deals with software Release policy having a Fixed Operational period after a Software System is released. The underlying Software Reliability Growth is described by J-M Model Optimal of Software Release Time minimizing Total Expected Cost is Obtained.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.27-35
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• 1989

Software developers often allocate a significant amount of effort to software testing. But for most business-related software system it is natural to expect the continued discovery of defects after the software system is released into field. Such defects are usually very expensive to fix and have the potential to cause great damages to the users. It is important to stop testing the software and release it to the users at the correct time. In this paper, we propose the determination of the optimal number of software test oy minimizing a total expected software cost. A numerical example is used when the criterion is the expected profit. The result indicates that the proposed software release policy based on the number of software test can be a good alternative to the existing policy.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.398-407
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• 2008

We consider a product recovery system that a single product is stocked in order to meet a demand from customers who may return products after usage. This paper addresses a problem of when to release a procurement process to replenish serviceable inventory and how many new products to procure. The structure of the optimal procurement policy is examined and numerically identified as a monotonic threshold curve. A numerical procedure is presented to jointly find the optimal procurement order size, optimal procurement policy, and optimal discounted profit. Sensitivity analysis also indicates that these optimal performance measurements have monotonic properties with respect to system parameters.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.159-166
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• 2013

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, finite failure non-homogeneous Poisson process model, presented and propose release policies of the life distribution, half-logistic property model which used to an area of reliability because of various shape and scale parameter. 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, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time. Software release time is used as prior information, potential security damages should be reduced.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.207-210
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• 2004

컴퓨터 소프트웨어는 이제 우리의 일상적인 삶에서 필수불가결한 요소이며 시스템의 운용에 중요한 요인이 되었다. 최근에 들어서는 소프트웨어 비용이 하드웨어 비용을 초과하게 되면서 소프트웨어를 개발하는데 필요한 비용과 더불어 소프트웨어 고장에 의한 비용의 중요성이 더 커지게 되었다. 본 논문에서는 Non-Homogeneous Poisson Process(NHPP)에 기초한 소프트웨어 비용 모형을 제안하려고 한다. 개발초기단계에서 출시 전까지의 소프트웨어 개발비용과 테스트비용, 출시이후의 보증기간동안의 제반비용, 소프트웨어 고장에 의한 위험비용 등을 포함하는 소프트웨어 비용 모형을 제안하고 소프트웨어의 최적 출시시기를 결정하는 효과적인 정책을 제시하려고 한다.

• IE interfaces
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• v.10 no.1
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• pp.119-134
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• 1997

The management of blood inventory is very important within the medical care system. The efficient management of blood supplies and demands for transfusions is of great economic and social importance to both hospitals and patients. For any blood type, there is a complex interaction among the optimal inventory level, daily demand level, daily supply level, transfusion to crossmatch ratio, crossmatch release period, issuing policy and the age of arriving units that determine the shortage and outdate rate. In this paper, we develop an efficient decision rule for blood inventory management in a hospital blood bank which can support efficient hospital blood inventory management using simulation. The primary use of the efficient decision rule will be to establish minimum cost function which consists of inventory levels, period in inventory, outdate and shortage rate for whole blood and various component inventories for a hospital blood bank or a transfusion service. If the administrator compute the mean daily demand for each blood type, the mean daily supply for each blood type, the length of the crossmatch release period and the average transfusion to crossmatch ratio, then it is possible to apply the efficient decision rule to compute the optimal inventory level, inventory period, outdate and shortage rate. This rule can also be used as a decision support system that allows the blood bank administrator to do sensitivity analysis related to controllable blood inventory parameters.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.13-27
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• 1996

The management of blood inventory is very important within the medical care system. The efficient management of blood supplies and demands for transfusion is of great economic and social importance to both hospitals and patients. Fro any blood type, there is a complex interaction among the optimal inventory level, daily demand level , daily supply level, transfusion to crossmatch ratio, crossmatch release period, issuing policy and the age of arriving units that determine the shortage and outdate rate. In this paper, we develop an efficient decision rule for blood inventory management in a hospital blood bank which can support efficient hospital blood inventory management using simulation, The primary use of the efficient decision rule will be to establish minimum cost function which consists of inventory levels , period in inventory, outdate and shortage rate for whole blood and various component inventories for a hospital blood bank or a transfusion service, If the adminstrator compute the mean daily demand for each blood type, the mean daily supply for each blood type, the length of the crossmatch release period and the average transfusion to crossmatch ratio , then it is possible to apply the efficient decision rule to compute the optimal inventory level, inventory period , outdate and shortage rate. This rule can also be used as a decision support system that allows the blood bank adminstrator to do sensitivity analysis related to controlled blood inventory parameters.