• Title/Summary/Keyword: Operations Research Models

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An Empirical Data Driven Optimization Approach By Simulating Human Learning Processes (인간의 학습과정 시뮬레이션에 의한 경험적 데이터를 이용한 최적화 방법)

  • Kim Jinhwa
    • Journal of the Korean Operations Research and Management Science Society
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    • v.29 no.4
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    • pp.117-134
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    • 2004
  • This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

An Approach to Composing a Structured Model from Validated Submodels

  • Suh, Chang-Kyo;Suh, Eui-Ho
    • Journal of the Korean Operations Research and Management Science Society
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    • v.15 no.2
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    • pp.85-95
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    • 1990
  • Structured modeling provides a formal mathematical framework, language, and computer-based environment for conceiving, representing, and manipulating a wide variety of model. It provides a natural framework for integrated modeling owing to its explicit representation power for computational dependencies among submodles. Nevertheless, it doesn't seem to offer a systematic way of composing a structured model from submodels. In order to develop a systematic way, this paper discusses three key issues : (1) Genus structure for model composition, (2) Storage of structured models, and (3) Integration of structured models. To formalize and visualize the approach, a programming module is developed to implemented the step-by-step integration.

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A Study on a Forecasting the Demand for the Future Mobile Communication Service by Integrating the Mobile Communication Technology (이동통신기술과의 연관성을 고려한 차세대 이동통신서비스의 수요예측에 관한 연구)

  • 주영진;김선재
    • Journal of the Korean Operations Research and Management Science Society
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    • v.29 no.1
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    • pp.87-99
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    • 2004
  • In this paper, we have developed a technology-service relationship model which describes the diffusion process of a group of services and relevant technologies, and have applied the developed model to the prediction of the number of subscribers to the next generation mobile service. The technology-service relationship model developed in this paper incorporates the developing process of relevant technologies, a supply-side factor, into the diffusion process of specific services, while many diffusion models and multi-generation diffusion models in previous researches are mainly reflect the demand-side factors. So, the proposed model could effectively applied to the telecommunication services where the developing of the relevant technologies are very essential to the service Penetration. In our application, the Proposed model provides a competitive substitution between the next generation mobile service and the traditional mobile service.

Flexible Mixed decomposition Method for Large Scale Linear Programs: -Integration of a Network of Process Models-

  • Ahn, Byong-Hun;Rhee, Seung-Kyu
    • Journal of the Korean Operations Research and Management Science Society
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    • v.11 no.2
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    • pp.37-50
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    • 1986
  • In combining dispersed optimization models, either primal or dual(or both) decomposition method widely used as an organizing device. Interpreting the methods economically, the concepts of price and resource-directive coordination are generally well accepted. Most of deomposition/ integration methods utilize either primal information of dual information, not both, from subsystems, while some authors have developed mixed decomposition approaches employing two master problems dealing primal and dual proposals separately. In this paper a hybrid decomposition method is introduced, where one hybrid master problem utilizes the underlying relationships between primal and dual information from each subsystem. The suggested method is well justified with respect to the flexibility in information flow pattern choice (some prices and other quantities) and to the compatibility of subdivision's optimum to the systemwide optimum, that is often lacking in conventional decomposition methods such as Dantzig-Wolfe's. A numerical example is also presented to illustrate the suggested approach.

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Effect of Power Dynamics in a Supply Chain on R&D and Market Performances (공급망 구성원 간 역학관계가 R&D 및 시장 성과에 미치는 영향)

  • Yoo, Seung Ho
    • Journal of the Korean Operations Research and Management Science Society
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    • v.41 no.1
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    • pp.113-126
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    • 2016
  • This study investigates the effect of power dynamics on R&D and market performances. Various types of relationships in a supply chain are considered. An R&D company offering new technology for product quality and a manufacturer responsible for both production and sales are utilized as subjects. The company with bargaining power differs with respect to the supply chain situation in practice, and no fixed single relationship and supply chain structure exist. However, only a few studies have considered the various relationships among players in a supply chain and their effects on performance. Therefore, we propose three models with different supply chain structures and power dynamics among players. This study contributes to the academia and supply chain practice by revealing the different characteristics of supply chain models.

K-1 Tank Life Cycle Cost Estimate Using PRICE Model (PRICE 모델을 이용한 K1전차 수명주기 비용추정)

  • 강창호;강성진
    • Journal of the military operations research society of Korea
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    • v.25 no.2
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    • pp.44-61
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    • 1999
  • Cost estimation has posed a significant challenge to estimators, planners, and managers in both government and military. Considerable historical evidence shows that accurate cost estimation has been difficult to achieve across a wide range of projects, including weapon systems. This paper introduces new cost estimating concept, CAIV(Cost As an Independent Variable) and a cost estimating case study using PRICE model, computer aided parametric estimating models(CAPE) for K1 tank cost estimate. CAIV concept is to set realistic but aggressive cost objectives easily in each acquisition program and to achieve cost, schedule, and performance objectives considering various managing risks with a project manager and industry teams. The Price model is one of computer aided cost estimating models and widely used in U.S. defense system analysis as a tool for CAIV. We analyze theories, inputs, outputs of the PRICE model and present a case study for K1 tank to estimate costs in requirement and concept phase, program and budgeting phase, and life cycle phase. Finally we obtain results that the Price model can be used in various phases of PPBEES depending upon available data and time.

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Performance Evaluation of Linear Regression, Back-Propagation Neural Network, and Linear Hebbian Neural Network for Fitting Linear Function (선형함수 fitting을 위한 선형회귀분석, 역전파신경망 및 성현 Hebbian 신경망의 성능 비교)

  • 이문규;허해숙
    • 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.

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Modeling Diffusion Process Under Abrupt Changes of External Factors (외생변수가 급변하는 상황에서의 확산과정 모형화)

  • Park Sang-June;Hahn Min-Hi;Shin Chang-Hoon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.2
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    • pp.15-26
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    • 2006
  • In reality, we can observe anomalous diffusion patterns of cycle-recycle or rejuvenation. Abrupt changes in the market environment such as sudden currency devaluation or change in government policy or those in marketing strategies such as drastic repositioning can lead to such atypical diffusion patterns. The authors present extended Bass models that incorporate effects of such abrupt changes of external factors into the hazard rate and the market potential. Using a set of compact-car data affected by a drastic change in the government policy, they illustrate the strengths of the proposed models.

Selection of Important Variables in the Classification Model for Successful Flight Training (조종사 비행훈련 성패예측모형 구축을 위한 중요변수 선정)

  • Lee, Sang-Heon;Lee, Sun-Doo
    • IE interfaces
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    • v.20 no.1
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    • pp.41-48
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    • 2007
  • The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

An Optimal Surveillance Units Assignment Model Using Integer Programming (정수계획법을 이용한 최적 감시장비 배치모형에 관한 연구)

  • 서성철;정규련
    • Journal of the military operations research society of Korea
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    • v.23 no.1
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    • pp.14-24
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    • 1997
  • This study is to develop an optimal surveillance units assignment model in order to obtain the maximized surveillance efficiency with the limited surveillance units. There are many mathematical models which deal with problems to assign weapons such as aircrafts, missiles and guns to targets. These models minimize the lost required to attack, the threat forecast from the enemy, or both of them. However, a problem of the efficient assignment of surveillance units is not studied yet, nevertbless it is important in the battlefield surveillance system. This paper is concerned with the development of the optimal surveillance units assignment model using integer programming. An optimal integer solution of the model can be obtained by using linear programming and branch and bound method.

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