• Korean Management Science Review
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• v.11 no.3
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• pp.103-128
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• 1994

Due to the trend of evolution toward a broadband communication network with fiber-optics, the design and operation of fiber-optic network have been received a great deal of research attention recently. Furthermore, even a single fiber link failure in the network may result in severe service loss. Thus, the network survivability becomes an importantissue in planning and designing the network. This survey is on modelling of various fiber-optic subscriber loop network(FSLN) design problems, which are essential ones for providing broadband communication services and B-ISDN services. Models are classified and investigated as either conventional decomposition-iteration approach or integrated design method. To build survivable networks, SHR models are also suggested by ring control schemes. The result of this study will be effectively applied to build a design model for FSLN in the practical applications.

• Journal of Information Technology and Architecture
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• v.10 no.2
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• pp.169-180
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• 2013

The effectiveness of joint operations depends on Jointness based on interoperable elements of participating forces. Many specialists have actively done research studies on interoperability measurement models with the goal of straightforward way of measuring and then have improved the interoperability of elements based on DOTMLPF-p (Doctrine, Organization, Training, Materiel, Leadership & Education, Personnel, Facilities, Policy) in the forces. After the survey of 16 interoperability measurement models, we have concluded that most of them applied only a small portion of DOTMLPF-p elements explicitly or all portions of DOTMLPF-p elements implicitly. In this study, we propose a conceptual interoperability measurement model for applying all DOTMLPF-p elements explicitly. And it can evaluate not only the level of interoperability among forces but also level of jointness for joint operations.

• Journal of the military operations research society of Korea
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• v.36 no.1
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• pp.51-64
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• 2010

In this paper, we investigate and analyze the application of VV&A on the development of war-game models which were developed in Korea. Then we propose VV&A framework which comprises VV&A basic model, VV&A reference model and a supporting tool. The VV&A basic model consists of VV&A process, products and methodologies. The VV&A reference model includes VV&A check lists for each VV&A activities, an assessment model of VV&A execution level and VV&A process maturity model. The VV&A supporting tool is to document and manage VV&A products. The proposed VV&A framework can be used as the foundation of VV&A plan on its execution.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.163-173
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• 1997

Although numerous studies demonstrate that one technique outperforms the others for a given data set, it is hard to tell a priori which of these techniques will be the most effective to solve a specific problem. It has been suggested that the better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the predictive performance. This paper proposes the post-model integration method, which tries to find the best combination of the results provided by individual techniques. To get the optimal or near optimal combination of different prediction techniques, Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an object function subject to numerous hard and soft constraints. This study applies three individual classification techniques (Discriminant analysis, Logit model and Neural Networks) as base models for the corporate failure prediction. The results of composite predictions are compared with the individual models. Preliminary results suggests that the use of integrated methods improve the performance of business classification.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.41-60
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• 2004

A stream data is a data set that is accumulated to the data storage from a data source over time continuously. The size of this data set, in many cases. becomes increasingly large over time. To mine information from this massive data. it takes much resource such as storage, memory and time. These unique characteristics of the stream data make it difficult and expensive to use this large size data accumulated over time. Otherwise. if we use only recent or part of a whole data to mine information or pattern. there can be loss of information. which may be useful. To avoid this problem. we suggest a method that efficiently accumulates information. in the form of rule sets. over time. It takes much smaller storage compared to traditional mining methods. These accumulated rule sets are used as prediction models in the future. Based on theories of ensemble approaches. combination of many prediction models. in the form of systematically merged rule sets in this study. is better than one prediction model in performance. This study uses a customer data set that predicts buying power of customers based on their information. This study tests the performance of the suggested method with the data set alone with general prediction methods and compares performances of them.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.7-22
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• 2014

By the publications of RDF and OWL, the Semantic Web is confirmed as a technology through which information in the Internet can be processed by machines. The focus of the Semantic Web study after then has moved to how to provide more useful information to users for their decision making beyond simple use of the structured data in ontologies. SWRL that makes logical inference possible by rules, and SWCL that formulates constraints under the Semantic Web environment are some of many efforts toward the achievement of that goal. Constraint represents a connection or a relationship between individual data in ontology. Based on SWCL, this paper tries to extend the language by adding one more type of constraint, implication constaint, in its repertoire. When users use binary variables to represent logical relationships in mathematical models, it requires and knowledge on the solver to solve the models. The use of implication constraint ease this difficulty. Its need, definition and relevant technical description is presented by the use of the optimal common attribute selection problem in product design.

• Journal of the military operations research society of Korea
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• v.6 no.1
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• pp.93-101
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• 1980

An effectively designed budget system in the poor resources environment necessarily has three design criteria : (i) to be both planning-oriented and control-oriented, (ii) to be both rationalistic and realistic, (iii) to be sensitive to the variations of resources environment. PPB system is an extreme (planning-oriented and rationalistic) and conventional OEB/OUB system is the other extreme (control-oriented and incrementalistic). Generally, the merits of rationalism are limited because of the infeasibility of applications. Hence, mixtures of the two extremes such as MBO, ZBB, and RZBB have been examined and applied during the last decade. The classical mathematical models of capital budgeting are the starting points of the development of the Budget-Mix Model introduced in this paper. They are modified by the followings: (i) technological-resource constraints, (ii) bounded-variable constraint, (iii) the exchange rules. Special emphasis is laid on the above (iii), because we need more efficient interresource exchanges in the budget-mix process. The Budget-Mix Model is not based on optimization, but a heuristic approach which assures a satisficing solution. And the application fields of this model range between the incremental Nonzero-Base Budgeting and the rational Zero-Base Budgeting. In this thesis, the author suggests 'the budget- mix concept' and a budget-mix model. Budget-mix is a decision process of making program-mix and resource-mix together. For keeping this concept in the existing organization realistic, we need the development of quantitative models describing budget-mix situations.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.145-156
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• 2015

Incorporation of individual learning and forgetting behaviors within worker-task assignment models produces a mixed integer nonlinear program (MINLP) problem, which is difficult to solve as a NP hard due to its nonlinearity in the objective function. Previous studies commonly assume homogeneity among workers in workforce scheduling that takes account of learning and forgetting characteristics. This paper expands previous researches by considering heterogeneous individual learning/forgetting, and investigates the impact of worker heterogeneity in initial expertise, steady-state productivity, learning and forgetting on system performance to assist manager's decision-making in worker-task assignments without tackling complex MINLP models. In order to understand the performance implications of workforce heterogeneity, this paper examines analytically how heterogeneity in each of the four parameters of the exponential learning and forgetting (L/F) model affects system performance in three cases : consecutive assignments with no break, n breaks of s-length each, and total b break-periods occurred over T periods. The study presents the direction of change in worker performance under different assignment schedules as the variance in initial expertise, steady-state productivity, learning or forgetting increases. Thus, it implies whether having more heterogenous workforce in terms of each of four parameters in the L/F model is desired or not in different schedules from the perspective of system productivity measurement.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.595-598
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• 2004

In recognizing knowledge as a new resource in gaining organizational competitiveness, knowledge management suggests a method in managing and applying knowledge for improving organizational performance. Much knowledge management research has focused on identifying, storing, and disseminating process related knowledge in an organized manner. Applying knowledge to decision making has a significant impact on organizational performance than solely processing transactions for knowledge management. In this research, we suggest a method of knowledge-based decision-making using system dynamics, with an emphasis to strategic problems. The proposed method transforms individual mental models into explicit knowledge by translating partial and implicit knowledge into an integrated knowledge model. The scenario-based test of the organized knowledge model enables decision-makers to understand the structure of the target problem and identify its basic cause, which facilitates effective decision-making. This method facilitates the linkage between knowledge management initiatives and achieving strategic goals and objectives of an organization.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.55-69
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• 2009

It is often to apply revenue sharing models in rental industries which consist of a retailer and a wholesaler. This research analyzed the influences to profit of the supply chain if we adopt the revenue sharing model when the demand is uncertain and price sensitive. We found the conditions of the revenue sharing model to maximize the profit of the supply chain, and identified incentive compatible conditions for revenue sharing. It is proved that vertical integration guarantees maximization of profit for the supply chain. Also we found that it is possible to derive Incentive compatible schemes by controlling ranges of revenue sharing ratios.