• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.380-383
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• 2003

In this paper, we propose a fuzzy group decision making method for multiple decision maker-multiple objective programming problems to obtain the agreeable solution. In the proposed method, considering the vague nature of human subjective judgement it is assumed that each of multiple decision makers has a fuzzy goal for each of his/her own objective functions. After eliciting the membership functions from the decision makers for their fuzzy goals, total M-Pareto optimal solution concept is defined in membership spaces in order to deal with multiple decision maker-multiple objective programming problems. For generating a candidate of the agreeable solution which is total M-Pareto optimal, the extended weighted minimax problem is formulated and solved for some weighting vector which is specified by the decision makers in their subjective manner, Given the total M-Pareto optimal solution, each of the derision makers must either be satisfied with the current values of the membership functions, or update his/her weighting vector, However, in general, it seems to be very difficult to find the agreeable solution with which all of the decision makers are satisfied perfectly because of the conflicts between their membership functions. In the proposed method, each of the decision makers is requested to estimate the degree of satisfaction for the candidate of the agreeable solution. Using the estimated values or satisfaction of each of the decision makers, the core concept is desnfied, which is a set of undominated candidates. The interactive algorithm is developed to obtain the agreeable solution which satisfies core conditions.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.76-85
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• 2016

This paper presents a method of decision on where bus splitting is needed to reduce fault current level of power systems and to satisfy the fault current constraints. The method employs a modified fault current constrained optimal power flow (FCC-OPF) with X variables for the candidate locations of splitting and for decision making on whether to split or not, it adopts soft-discretization by augmenting inversed U-shaped penalty terms. Also, this paper discusses the procedure on the adequate selection of bus splitting locations based on the results of the modified FCC-OPF, to reduce the total number of the actions taken.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.71-76
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• 2011

The problem of decision making under imprecise environments are widely spread in real life decision situations. We present a method of object recognition from imprecise multi observer data, which extends the work of Roy and Maji [J Compu. Appl. Math. 203(2007) 412-418] to generalized intuitionistic fuzzy soft set theory. The method involves the construction of a comparison table from a generalized intuitionistic fuzzy soft set in a parametric sense for decision making.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.141-156
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• 2002

This article deals with the multiple alternative proposal of Venture Business policy. when Decision makers meet a very complex and important business to take a good choice. It might not be easy that we make a decision and accept the decision as an exact result of analysis at a complication and uncertain situation. This is the reason why the original research use Statistical Survey method and Visual Decision Making Process(VDMP) to improve decision analysis method. Therefore, Our research suggests that the VDMP utilized in the strategic decision making situation as a group decision adding tool, can be applied in the development of a process vision and implementation plan. as a result, researcher describe step by step the process of VDMP

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.327-331
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• 2009

In fuzzy logic, aggregating uncertainties is generally achieved by means of operators such as t-norms and t-conorms. However, existing aggregation operators have some disadvantages as follows : First, they are situation-independent. Thus, they may not be properly applied to dynamic aggregation process. Second, they do not give an intuitional sense to decision making process. To solve these problems, we propose a new $\varepsilon$-AMDA (Aggregation based on the fuzzy Multidimensional Decision Analysis) algorithm to reflect degrees of strength for option i (i = 1, 2, ..., n) in the decision making process. The $\varepsilon$-AMDA algorithm makes adaptive aggregation results between min (the most weakness for an option) and max (the most strength for an option) according to the values of the parameter representing degrees of strength for an option. In this respect, it may be applied to dynamic aggregation process. In addition, it provides a mechanism of the fuzzy multidimensional decision analysis for decision making, and gives an intuitional sense to decision making process. Thus, the proposed method aids the decision maker to get a suitable decision according to the degrees of strength for options (or alternatives).

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.89-97
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• 2022

Recently, various problems such as reduced productivity, insufficient inflow of skilled manpower, reduced quality, and concerns about increasing safety accidents have appeared in the domestic construction industry. Stakeholder of construction project are considering the Off-Site Construction (OSC) method rather than the conventional on-site construction as an alternative. Despite the importance of decision making in the early stage of the adoption of OSC, there is a lack of methodologies for rational decision making. In this study, a decision making system has been developed to derive the final construction cost score by deriving the project characteristics, selecting the construction difficulty index, and developing a cost model for each construction method alternatives to calculate the standard construction cost. Using this system, the OSC method can be effectively evaluated in terms of its feasibility in the early stage of construction

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.17-26
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• 2018

Purpose - The purpose of this study is to provide a formalized process of decision making for companies or organizations that need to make various decisions in the age of uncertainty. Therefore, this study aimed to proposes a strategic decision-making approach citing the relatively easily accessible using IPA(important-performance analysis) and SWOT/AHP analysis. Research design, data, and methodology - To be specific, the first step is to derive necessary attributes and conduct IPA. The second step is to subdivide the IPA results into internal strength and weakness factors and the external opportunity and threat factors, hierarchize those factors, and weight them accordingly. The third step is to build a causality model to propose a method of supporting a rational decision making. Results - The foregoing approach seems to facilitate the diversification of decision-making strategies by helping businesses or organizations to measure and analyze the attributes needed for certain decisions. Additionally, the perceived importance and satisfaction (or achievement) usage of those derived attributes can be used as the reference data for SWOT/AHP analysis. Conclusions - The proposed stepwise approach is applicable to businesses or organizations in need of making stepwise decisions in line with their retained competencies in comparison to conventional or intuitive decision-making practices.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.100-114
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• 2007

Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation-enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision-making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.47-55
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• 2016

As one of recent issues in the information and communication industry, internet of things has attracted attention to provide intelligent infrastructure services which connect and share data and information between real and virtual world. According to the development of these internet of things technologies, types of machines, telecommunication devices, and terminals are increasing tremendously. In this situation, connectivity and interoperability between internet of things components are important issues to build a hyper connected society. To visualize this society, it is important to set up and develop information and communication technology (ICT) standards among stakeholders. However, under limited budget and human resources, it is essential to rank standardization work items for setting standards with respect to efficiency. The purpose of this study is to provide a method for setting standardization strategies within group decision making. As a multi-criteria group decision making tool, analytic hierarchy process (AHP) is adopted and applied to determine the priorities of setting work items. The proposed method first defines decision making problem with objective, criteria, and alternatives which produces a hierarchy consisting of upper and lower criteria. Then, pairwise comparisons of academy and public sector experts are performed with respect to their relative meaning and importance. Individual surveys of expert groups are collected and summarized to determine relative criteria importance measures. Furthermore, to deliver reliable importance criteria measures, differences between academy and public sector expert groups are compared and tested using Mann-Whitney non-parametric test. The results are illustrated for useful guidelines to practical group decision making in standardization strategy establishments.