• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.87-95
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• 2008

The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.148-151
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• 2003

Recently school food service operations are confronted with the wide spread pressures for accountability and the need to increase productivity. This paper is concerned with the make-or-buy decision framework for school food service systems considering the multi-attributes in the decision making. For the purpose of considering the multi-attributes analysis method in decision making for the school foodservice, we developed a make-or-buy decision framework using the multi-attribute analysis method, analytic hierarchy process, AHP method for school food service system. Finally, we developed a systematic and practical solution builder for a three-step decision support system in the view of 1) brainstorming for the idea generation, 2) analytic hierarchy process, AHP as a multi-attribute structure ed analysis method, and 3) aggregation logic model to integrate the results of reviewers. We developed web based program and applied it to a school foodservice problem.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.63-77
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• 1996

This study suggests that experts' group decision support system (Experts'GDSS) should be helpful to solve specific planning/design problems. Dealing with AHP (Analytic Hierarchical Process), as a group decision model, maximal covering model, as a facility allocation model, and GIS (Geographic Information System; ARC/INFO in this study), as a spatial representation model, this study seeks to examine the implication of GDSS (Group Decision Support System) in the housing facility allocation. The results of this study clearly demonstrated that experts' GDSS acted its positive role, systematically providing the relative weights among the planning variables and objectives. Among different expert groups (e.g., planners, scholars, and public administrators), this study showed that there were certain differences in their decision structures, which generated different solutions in facility allocation. The further study, however, remains to investigate the more systematic implementation of GDSS in planning problems; for example, reducing the conflicts between different groups with different purposes.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• Journal of the military operations research society of Korea
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• v.27 no.2
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• pp.37-55
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• 2001

The main purpose of this study is to review the current system and to develop a decision support system for evaluating the priorities among those possible alternatives in the army facility enterprise. This paper also provides an information system which can be effectively applied to various criteria and stages in decision making process such as Planning and Programming phases in PPBEES. The model base of decision support systems uses the concepts of the analytic hierarchy process along with the supplementary techniques such as TOPSIS and 0-1 integer programming. Both AHP and TOPSIS are used scoring approaches in the Planning phase and IP is induced at the Programming phase to give GO/NO-GO solution for each project. We use Expert Choice, Excel and LINDO s/w's to implement a prototyped model. The proposed methodology in this paper enables the decision makers to evaluate the priority based on quantitative and qualitative data in a systematic way.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.69-77
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• 2014

Because smart televisions (TVs) have various and innovative functions that are different from traditional TVs, consumers are front with a complex decision-making problem when they want to buy a best TV among alternatives made by many TV makers. TV manufactures have developed and announced different types of smart TV models and they need a comparative study for evaluating their characteristics. In this paper, we suggest the Analytic Hierarchy Process(AHP) method for deciding the best smart TVs regarding many selection criteria. The method provides a decision support for consumers who like to purchase a smart TV. We describe criteria affecting the smart TV selection through a literature review and suggest a user testing method in order to derive accurate judgments from consumers. Using the Expert Choice software package, we show a an numerical example how the priority of smart TVs are computed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3196-3203
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• 2010

The regional strategic industry support has been increasingly developed due to the change of environmental and political conditions for the last 10 years. As the paradigm changed from the central government-sponsored system to regional government-sponsored system, the policy has been diversified into various support systems such as regional strategic industry, specialized industry, supporting technology, supporting business, etc. It is crucial to establish the overall development plans and project strategies for the regional industry in terms of effectiveness and efficiency which will generate an integrated strategic frame to adjust overlapped supporting policies and offer a consumer-oriented service. Not only does the study focus on performance-based outcome regarding to a regional business (supporting policy) portfolio, but it also analyzes and proves an empirical decision-making model to draw out the priority and relative importance according to the regional strategic industry and support cases by analyzing the case of Chungnam area's strategic industry support in 2009. Following a priority list of 20 support cases selected from this research model by the Analytic Hierarchy Process (AHP), the result shows that the diverse support plans are needed according to the different strategic industries or the size of enterprise due to the fact that priority of project type varies upon the characteristics of strategic industry. Thus, the support project needs to generate various strategic industries and develop differentiated support policy to consolidate competitiveness of regional enterprises and revitalize the regional economy.

• Korean Management Science Review
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• v.13 no.3
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• pp.75-90
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• 1996

This paper presents an improved method of the Analytic Hierarchy Process (AHP) when customers are to select the best automobile purchase models. In order to support group decisions and as a different procedure of the conventional AHP, we combine the AHP model with a spreadsheet model that applies the Likert's rating scheme to each alternative. We only consider individual pairwise comparison matrices where the consistency ratio (C.R.) is less than or equal to 0.2. Finally, we regard the weight of each decision maker as a reciprocal number of C.R. As a case study we prioritize three passenger cars of medium size in the domestic market. The major evaluation criteria include:exterior or interior features, performance, safety, pricing, salesman, and after service.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.155-171
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• 2012

With the continuous and outstanding development of information technology(IT), human being is coming to the new computing era which is called cloud computing. This era brings lots of huge benefits also at the same time release the resources of IT infrastructure and data boom for man. In the future no longer, most of IT service providers, enterprises, organizations and systems will adopt this new computing model. There are three main deployment models in cloud computing including public cloud, private cloud and hybrid cloud; each one also has its own cons and pros. While implementing any kind of cloud services, customers have to choose one of three above deployment models. Thus, our paper aims to represent a practical framework to help the adopter select which one will be the best suitable deployment model for their requirements by evaluating each model comprehensively. The framework is built by applying the analytic hierarchy process(AHP), namely benefit-cost-opportunity-risk(BCOR) model as a powerful and effective tool to serve the problem. The gained results hope not only to provide useful information for the readers but also to contribute valuable knowledge to this new area. In addition, it might support the practitioners' effective decision making process in case they meet the same issue and have a positive influence on the increase of right decision for the organization.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.855-861
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• 2005

Every public agency governing infrastructure has to plan effectively for rehabilitation of existing facilities within the constraints of the capital program. Numerous technical, social, political, financial, and management constraints govern the decision to rehabilitate a facility. However, without a systematic procedure for selecting facilities for rehabilitation, within the prevailing constraints, it is possible that the funds available for rehabilitation might be suboptimized. Therefore, a decision support system that assists the user in selecting facilities for rehabilitation while considering the technical, social, financial, and political and management constraints will be useful in the decision-making process. This paper compares the Analytical Hierarchy Process (AHP) with the Swing Weight method used to prioritize functional criteria for suburban station rehabilitation. This paper also contains a brief discussion about the relevance of the Multi Attribute utility theory in developing a decision model for the problem at hand. The results of this paper provides the user with a decision support system that would prioritize the stations in order of their weights obtained by a systematic evaluation of various criteria and sub-criteria involved in the decision making process