• Journal of the military operations research society of Korea
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• v.37 no.1
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• pp.119-128
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• 2011

This paper deals with a study on mission analysis considering the effectiveness measurement of UAV system operations. This mission analysis process is composed of 5 steps; (1) creation of a base model in MANA, (2) design of input parameter set using experiment design, (3) mapping input parameter set to the MANA scenario file, (4) data farming and model run in batch process, and (5) statistical analysis of the simulation result. In the result of this study, the effect of input parameter to the dependent parameter was shown to decrease in the order classification range, sweep width, height, speed, FOV(Field of view), and classification probability. The study also shows that the operational effectiveness of an improved scenario proposed can increase 10.2% from the base scenario.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.1-12
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• 2012

In this paper, we report a case study on the common due-date assignment and scheduling problem in a paper remanufacturing system that produces corrugated cardboards using collected waste papers for a given set of orders under the make-to-order (MTO) environment. Since the system produces corrugated cardboards in an integrated process and has sequence-dependent setups, the problem considered here can be regarded as common due-date assignment and sequencing on a single machine with sequence-dependent setup times. The objective is to minimize the sum of the penalties associated with due-date assignment, earliness, and tardiness. In the study, the earliness and tardiness penalties were obtained from inventory holding and backorder costs, respectively. To solve the problem, we adopted two types of algorithms: (a) branch and bound algorithm that gives the optimal solutions; and (b) heuristic algorithms. Computational experiments were done on the data generated from the case and the results show that both types of algorithms work well for the case data. In particular, the branch and bound algorithm gave the optimal solutions quickly. However, it is recommended to use the heuristic algorithms for large-sized instances, especially when the solution time is very critical.

• The Journal of Society for e-Business Studies
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• v.3 no.1
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• pp.1-22
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• 1998

SDAI (Standard Data Access Interface) is an interface specification of accessing various storage systems such as file systems and database management systems for STEP data. Using SDAI, both application program developers and CAD/CAM system developers can be relieved from dealing with STEP physical file or system dependent DBMS operations. In this paper, we present implementations of SDAI on different data models, i.e., relational, extended relational, and object-oriented. In order to implement SDAI, we need to translate the EXPRESS information model into target data models. The schema translation process for three different data models are compared and other implementation issues are discussed.

• Journal of Information Technology Applications and Management
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• v.20 no.3_spc
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• pp.169-185
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• 2013

In this research, for find out how operations efficiency for ERP systems, after introducing ERP to manufacturing firms with DEA technique. According to research analyzed relative time dependent efficiency, using Time Window Analysis. And for company group and the other firm within the each same Industry, the relative effectiveness of each company group establishment was compared using DEA.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.67-81
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• 2010

In Schumpeterian competition, superior profit arises from successful innovation created by firm's R&D strategy. Such R&D strategy diverges as time passes. This study examines empirically the effects of diverged forms of R&D strategy such as technological assets, technological diversity, and technological similarity on firm performance in Korean pharmaceutical industry. With the financial and patent data of 96 firms for 14 years from 1994 to 2007, we measured variables. And then we performed panel analysis with 3 years lag between dependent variable and other variables. The result shows that firm performance increases as technological asset and technological diversification increase. But technological similarity positively affects on firm performance in opposition to our hypothesis. We interpret and discuss these results and highlight the theoretical and practical implications of our findings.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.17-29
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• 1995

Recently, neural network models have been employed as an alternative to regression analysis for point estimation or function fitting in various field. Thus far, however, no theoretical or empirical guides seem to exist for selecting the tool which the most suitable one for a specific function-fitting problem. In this paper, we evaluate performance of three major function-fitting techniques, regression analysis and two neural network models, back-propagation and linear-Hebbian-learning neural networks. The functions to be fitted are simple linear ones of a single independent variable. The factors considered are size of noise both in dependent and independent variables, portion of outliers, and size of the data. Based on comutational results performed in this study, some guidelines are suggested to choose the best technique that can be used for a specific problem concerned.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.99-109
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• 1992

It is very important in the navy operation to forecast and allocate appropriate petroleum requirements of a certain class of ships for the next year. The amount of petroleum requirements is very much dependent on the number of operating and training days or the running time of the main engine and the gas turbine of the ship. Two regression models were estimated and analyzed from real data obtained from several ships operated during the past three years. Finally, the amount of petroleum requirements that a ship is expected to spend for the next year can be estimated by using this estimated regression model based on operating hours of main engines and gas turbines of the ship.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.102-106
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• 1997

Grinding has difficulty in satisfying the qualitative knowledge based on the skilled expert as well as quantitative data for all user. Design of grinding database is based on the frame-based model for utilizing the empirical and qualitative knowledge. Inthis paper, basic strategy to develop the grinding database by frame-based model, which is strongly dependent upon experience and intuition, frame-base model, which is strongly dependent upon experience and intuition, is described. Design of grinding database is based on the frame-based model for utilizing the ambiguous knowledge and inference is accomplised by the object-oriented paradigm system.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.19-35
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• 2006

We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.306-310
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.