• Title/Summary/Keyword: Management & operations step

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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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Development of a Cross-impact Hierarchical Model for Deciding Technology Priority (기술우선도 결정을 위한 상호영향 계층분석모형의 개발)

  • 권철신;조근태
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.1
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    • pp.1-17
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    • 2002
  • The objective of this paper is to develop a new priority setting algorithm that considers the cross-impact of the future technology alternatives and that satisfies the final goal of the technology management through multi-hierarchy evaluation criteria. By combining the Analytic Hierarchy Process (AHP) model, which is a well-known priority setting model, and Cross Impact Analysis (CIA) model, which is a technological forecasting method that considers cross-impact among R&D Items, we developed an Integrated Cross-Impact Hierarchical (CIH) model, which sets the priority by considering technological forecasting and technology dependency simultaneously. A step-by-step numerical example of the model developed here is presented as backup of its practicality.

Splitting Algorithm Using Total Information Gain for a Market Segmentation Problem

  • Kim, Jae-Kyeong;Kim, Chang-Kwon;Kim, Soung-Hie
    • Journal of the Korean Operations Research and Management Science Society
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    • v.18 no.2
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    • pp.183-203
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    • 1993
  • One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.

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Web-based Three-step Project Management Model and Its Software Development

  • Hwang Heung-Suk;Cho Gyu-Sung
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.373-378
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    • 2006
  • Recently the technical advances and complexities have generated much of the difficulties in managing the project resources, for both scheduling and costing to accomplish the project in the most efficient manner. The project manager is frequently required to render judgments concerning the schedule and resource adjustments. This research develops an analytical model for a schedule-cost and risk analysis based on visual PERT/CPM. We used a three-step approach: 1) in the first step, a deterministic PERT/CPM model for the critical path and estimating the project time schedule and related resource planning and we developed a heuristic model for crash and stretch out analysis based upon a time-cost trade-off associated with the crash and stretch out of the project. 2) In second step, we developed web-based risk evaluation model for project analysis. Major technologies used for this step are AHP (analytic hierarchy process, fuzzy-AHP, multi-attribute analysis, stochastic network simulation, and web based decision support system. Also we have developed computer programs and have shown the results of sample runs for an R&D project risk analysis. 3) We developed an optimization model for project resource allocation. We used AHP weighted values and optimization methods. Computer implementation for this model is provided based on GUI-Type objective-oriented programming for the users and provided displays of all the inputs and outputs in the form of GUI-Type. The results of this research will provide the project managers with efficient management tools.

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An Ant Colony Optimization Algorithm to Solve Steiner Tree Problem (스타이너 트리 문제를 위한 Ant Colony Optimization 알고리즘의 개발)

  • Seo, Min-Seok;Kim, Dae-Cheol
    • Journal of the Korean Operations Research and Management Science Society
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    • v.33 no.3
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    • pp.17-28
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    • 2008
  • The Steiner arborescence problem is known to be NP-hard. The objective of this problem is to find a minimal Steiner tree which starts from a designated node and spans all given terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step, graph reduction rules eliminate useless nodes and arcs which do not contribute to make an optimal solution. In the second step. ant colony algorithm with use of Prim's algorithm is used to solve the Steiner arborescence problem in the reduced graph. The proposed method based on a two-step procedure is tested in the five test problems. The results show that this method finds the optimal solutions to the tested problems within 50 seconds. The algorithm can be applied to undirected Steiner tree problems with minor changes. 18 problems taken from Beasley are used to compare the performances of the proposed algorithm and Singh et al.'s algorithm. The results show that the proposed algorithm generates better solutions than the algorithm compared.

A Modified Gradient Precedure for Multifacility Euclidean Distance Location Problems

  • Lee, Chae Y.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.13 no.2
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    • pp.25-33
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    • 1988
  • An efficient heuristic solution procedure is developed for the minimum location problems. The gradient direction method and modified gradient approach are developed due to the differentiability of the objective functions. Suboptimal step size is obtained analytically. A Modified Gradient Procedure (NGP) is presented and compared with the hyperboloid approximation procedure (HAP) which is one of the best known methods.

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A study on the variations of a grouping genetic algorithm for cell formation (셀 구성을 위한 그룹유전자 알고리듬의 변형들에 대한 연구)

  • 이종윤;박양병
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.11a
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    • pp.259-262
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    • 2003
  • Group technology(GT) is a manufacturing philosophy which identifies and exploits the similarity of parts and processes in design and manufacturing. A specific application of GT is cellular manufacturing. the first step in the preliminary stage of cellular manufacturing system design is cell formation, generally known as a machine-part cell formation(MPCF). This paper presents and tests a grouping gentic algorithm(GGA) for solving the MPCF problem and uses the measurements of e(ficacy. GGA's replacement heuristic used similarity coefficients is presented.

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Cascade-Correlation Network를 이용한 종합주가지수 예측

  • 지원철;박시우;신현정;신홍섭
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.745-748
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    • 1996
  • Korea Composite Stock Price Index (KOSPI) was predicted using Cascade Correlation Network (CCN) model. CCN was suggested, by Fahlman and Lebiere [1990], to overcome the limitations of backpropagation algorithm such as step size problem and moving target problem. To test the applicability of CCN as a function approximator to the stock price movements, CCN was used as a tool for univariate time series analysis. The fitting and forecasting performance fo CCN on the KOSPI was compared with those of Multi-Layer Perceptron (MLP).

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A K-means-like Algorithm for K-medoids Clustering

  • Lee, Jong-Seok;Park, Hae-Sang;Jun, Chi-Hyeok
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.10a
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    • pp.51-54
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    • 2005
  • Clustering analysis is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. In this paper we propose a new algorithm for K-medoids clustering which runs like the K-means algorithm. The new algorithm calculates distance matrix once and uses it for finding new medoids at every iterative step. We evaluate the proposed method using real and synthetic data and compare with the results of other algorithms. The proposed algorithm takes reduced time in computation and better performance than others.

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Development a Customer-Supplier Partnership Survey

  • 정승호;배경율
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.197-200
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    • 1998
  • The purpose of this paper is to develop a customer-supplier partnership survey. To achieve this purpose, a customer-supplier partnership model is first proposed. And then, based on the partnership model proposed, each step that was taken to develop the customer-supplier partnership survey is described.

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