• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.173-183
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• 2004

Data envelopment analysis(DEA) is a mathematical programming approach to asses s relative efficiency of a group of decision-making units. In view of the defects of existing models in evaluating efficiency of the system with P independent subsystems, Yang et al. [10] introduced YMK model with the assumption that decision-making unit(DMU) is independent of each other. But in some production systems, decision-making units usually have some relationships in this way or that. In this paper, DEA model is given by assuming that DMUs can cooperate with others in its subgroups. Some property and the efficiency relationship of the whole system and its subsystems are given.

• Korean Management Science Review
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• v.12 no.2
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• pp.147-164
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• 1995

There have been two dominant paradigms in understanding and modeling an expert's decision-making behavior: output analysis and process-tracing. While the two paradigms are complementary, they have not been used yet in a combined manner. This study extends the previous research work in the two paradigms to inductive modeling research by 1) analyzing individual experts' decision strategies, 2) comparing performance of four popular inductive modeling methods, and 3) matching their performance against the type of decision strategy employed by experts.

• Korean Journal of Adult Nursing
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• v.15 no.2
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• pp.236-246
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• 2003

Purpose: The purpose of this study was to examine the differences of the process of change, decision making, self-efficacy and perception of subjective health according to the stages of exercise behaviors suggested by transtheoretical models among older adults. Method: The subjects consisted of 291 older adults. Trained research assistants interviewed the older adults using structured questionnaires. ANOVA analyses with post hoc test were used to examine the mean differences for each stage of exercise behavior using SPSS for windows. Result: The subjects were divided into five stages of exercise behavior: 24.4% precontemplation, 12.4% contemplation, 17.9% preparation, 12.4% action, 33.0% maintenance stage. There were significant differences in process of change, decision making, self-efficacy and subjective health perception according to the exercise stage of change. 'Self-liberation' and 'stimulus control' were important strategies for intention of exercise, while 'reinforcing management' for the actual practice of exercise. 'Self-efficacy' was an effective strategy to change older adults from pre-contemplation to preparation stage. Conclusion: For exercise intervention, older adults should be classified into groups according to their stages of exercise behaviors and provided effective individualized intervention depending on their stage.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.203-210
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• 2014

This study proposes adaptive decision making method having feed-back structure of regression and simulation models to support the quick decision making of production managers by managing and integrating the mutual relationship among historical data. For that, from historical data that have extracted and accumulated from each process, we first selected major constraint resources that are used as independent variables in regression model. The regression model is designed by using the dependent variables (objectives) that defined above by managers and independent variables selected in previous step and simulation model that are composed of constraint resources is designed. In process of simulation run, we obtain the multiple feasible solutions (alternatives) by using meta-heuristic method. Each solution is substituted by regression equation and we found the optimal solution that is minimum of difference between values obtained by regression model and simulation results. The optimal solution is delivered and incorporated to production site and current operation results from production site is used to generate new regression model after that time.

• Journal of Korea Water Resources Association
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• v.41 no.2
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• pp.127-135
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• 2008

The objective of sewer rehabilitation is to improve its function while eliminating inflow/infiltration (I/I) and insufficient carrying capacity (ICC). Such rehabilitation efforts, however, have not been particularly successful due to a lack of sewer data and unsystematic field practices. The present study aimed to solve these problems by developing a decision making model consisting of two models: the rehabilitation weighting model (RWM) and the rehabilitation priority model (RPM). In RWM, the I/I of each pipe in a drainage district is estimated according to various defects, with each defect given an individual weighting factor using an analytic hierarchy process (AHP). RPM determines the optimal rehabilitation priority (ORP) using a genetic algorithm (GA). The developed models can be used to overcome the problems associated with unsystematic practices and, in practice, as a decision making tool for urban sewer system rehabilitation.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.47-57
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• 2013

Big data analysis needs a new tool for decision making in view of data volume, speed, and variety. Many global IT enterprises are announcing a variety of Big data products with easy to use, best functionality, and modeling capability. Big data packages are defined as a solution represented by analytic tools, infrastructures, platforms including hardware and software. They can acquire, store, analyze, and visualize Big data. There are many types of products with various and complex functionalities. Because of inherent characteristics of Big data, selecting a best Big data package requires expertise and an appropriate decision making method, comparing the selection problem of other software packages. The objective of this paper is to suggest a decision making method for selecting a Big data package. We compare their characteristics and functionalities through literature reviews and suggest selection criteria. In order to evaluate the feasibility of adopting packages, we develop two Analytic Hierarchy Process(AHP) models where the goal node of a model consists of costs and benefits and the other consists of selection criteria. We show a numerical example how the best package is evaluated by combining the two models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.49-63
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• 1985

This paper is focused on the introduction of the types of models and explanation of the fundamental concepts and theory for development and use of the corporate planning and modeling system. Nowadays, a great deal of companies have been or experimenting with some form of a corporate planning and modeling system to support managerial and strategic decision making. From previous studies it was noted that most applications have tended to be financially based. This trend will probably continue. However, with the software and hardware currently available it is likely that companies will move more toward integrated models that link marketing, production, as will as financial areas. More emphasis will undoubtedly be placed on the use of econometric modeling, since this subelement of the overall planning and modeling process is closely tied to the market place and the economy. At any rate, wherever the development of corporate planning and modeling system is directed, clear understanding for the fundamental concepts and elements of the system is settled in advance in order to develope and use it.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.913-916
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• 2005

This paper presents the development of Artificial Neural Network models for forecasting the cost and contract duration of school reconstruction projects to assist the planners' decision-making in the early stage of the projects. 132 schools reconstruction projects in central Taiwan, which received the most serious damage from the Chi-Chi Earthquake, were collected. The developed Artificial Neural Network prediction models demonstrate good prediction abilities with average error rates under 10% for school reconstruction projects. The analytical results indicate that the Artificial Neural Network model with back-propagation learning is a feasible method to produce accurate prediction results to assist planners' decision-making process.

• Proceedings of the Korean System Dynamics Society
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• 2002.11a
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• pp.103-122
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• 2002

Construct ion sector government policies are targeted towards regulation than facilitation and management. This approach often fails to integrate different segments of the public and private and seems to be inadequate in encouraging the private sector to achieve better quality construction. This situation suggests a need for a better and systematic approach for construct ion policy making. This paper suggests a model-based approach to public policy making using system dynamics approach. Singapore government's policy making efforts to encourage the use of prefabrication are discussed as an application example. This paper presents system models which discuss strengths and weaknesses of the current construction system in Singapore using casual loops, and highlights the feedback processes that would be useful in decision making for the government. Based on these system dynamics models, this paper identifies four major potential policy interventions policy interventions.

• Journal of the military operations research society of Korea
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• v.2 no.1
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• pp.61-71
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• 1976