• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.55-61
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• 2003

The purpose of this paper is to propose a method for selecting the preferred alternatives of Multiple- Attribute Decision-Making(MADM) problem using the Entropy measure. A decision-maker who wants to estimate exactly the weight to be applied to her/his MADM problem is usually confronted with the embarrassing situation where, although there exist a variety of weighting methods, it is hard to find a right procedure to choose a pertinent value To remedy this uncomfortable situation, the Entropy measure commonly used in information theory, Is proposed as a tool that can be used by decision-makers to more efficiently select the preferred alternatives. As a result, the method proposed in the paper can be significant in that relatively easy to understand by decision-makers.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.37-44
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• 1990

In selecting the best project in multi-criteria decision making problems, the imperfect information of consequence and the vague preference of the decision maker(DM) would make the decision analysis more complex together with the conflict of several criteria. In this context, a method is proposed to deal the fuzzy information mentioned before instead of reducing it to a single representative value. And, based on the given imprecise information, projects are ranked completely or partially according to DM's vague preference. The procedure consists, for each pair of projects, of calculating the degree of supporting over all criteria and the degree of opposing with respect to each criterion for their outranking relation. Together with weights for each criterion, these indices produce fuzzy outranking relations for each pair of projects. And a complete or partial ranking of projects is obtained according to outranking degrees considering the interdependence among projects.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.973-988
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• 2023

In real-life scenarios, we may have to deal with real numbers or numbers in intervals or a combination of both to solve multi-criteria decision-making (MCDM) problems. Also, we may come across a situation where we must combine this interval and actual number membership values into a single real number. The most significant factor in combining these membership values into a single value is by using aggregation operators or scoring algorithms. To overcome such a situation, we suggest the cubic hypersoft set (CHSS) concept as a workaround. Ultimately, this makes it simple for the decision-maker to obtain information without misconceptions. The primary aim of this study is to establish some operational laws for the cubic hypersoft set, present the fundamental properties of aggregation operators and propose an algorithm by using the technique of order of preference by similarity to the ideal solution (TOPSIS) technique based on correlation coefficients to analyze the stress-coping skills of workers.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.274-283
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• 2002

This paper presents an efficient models for reinforeced concrete structures using CART-ANFIS(classification and regression tree-adaptive neuro fuzzy inference system). a fuzzy decision tree parttitions the input space of a data set into mutually exclusive regions, each of which is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the Predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it everywhere continuous and smooth. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.117-124
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• 2011

Supplier selection is one of the most important activities of a company. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer's company. In addition, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer. Therefore a performance evaluation system for supplier and green suppliers is necessary to determine the suitability of suppliers to cooperate with the company. Supplier and green supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in these problems make the decision making complicated. The objective of this study is to construct a decision-making process using fuzzy analytic hierarchy process (FAHP) and balanced scorecard (BSC) for evaluating supplier and green suppliers in the manufacturing industry. The BSC concept is applied to define the hierarchy with four major perspectives and performance indicators are selected for each perspective. FAHP is then proposed in order to tolerate vagueness and ambiguity of information. Finally, FAHP is applied to facilitate the solving process. With the proposed approach, manufacturers can have a better understanding of the capabilities that supplier and green supplier must possess and can evaluate and select the most suitable supplier for cooperation.

• 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

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.51-60
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• 1995

The key competition factor of manufacturing industries has progressively changed from cost to quality and time. Recently, the manufacturing environments more rapidly change than before. So, many companies want to introduce a advanced manufacturing system like CIMS to meet various user's needs and short delivery. But there is a considerable gap between the decision to invest and the achievement of promised benefits. Managers, generally, cannot afford CIM invesment unless they can determine beforehand that CIM will work in thier company and that will provide a coherent strategy and satisfactory return on investment In many cases, it is impossible to justify CIM investment by only economical analysis. Decision making problems like CIM investment are of a multiple objective nature. So, decision making process and multiattribute utility function are very useful methods to evaluate CIM justification In this paper, we described the key functions of CIM justification evaluation using IDEF methodology and developed the applicattion procedure of DMP and MUF method for CIM justification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1060-1064
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• 2009

This paper proposes a fuzzy AHP based decision-making model to select a telecommunication company and the target of the proposed model is university students in the capital area. When customers select a telecommunication company, they have difficulty in decision-making because there are many competitive and complementary factors of telecommunication companies. To select a best telecommunication company, customers need to consider a number of different quantitative and qualitative factors such as fare, various services, additional function, etc. In this study, we suggest a fuzzy AHP based decision-making model to select a telecommunication company considering various quantitative and qualitative factors. Especially, fuzzy theory is applied to deal with the unclear or ambiguous problems, and a linear normalization model is developed to convert the value of quantitative factors to fuzzy number. A empirical example which is the target of the university students in the capital area shows the feasibility of the proposed model and it can help customers to make better decision-making for their benefits.

• International Journal of Railway
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• v.7 no.1
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• pp.8-15
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• 2014

Recently, in the total railroad construction field, concrete slab tracks have been adapted in place of ballast tracks. Because ballast tracks need frequent maintenance and are difficult to handle due to increasing maintenance costs, eventually concrete slab tracks were selected as an alternative. However, owing to the hydration heat reactions and temperature-affected shrinkage of the concrete, a variety of studies to solve maintenance problems related to concrete slab tracks are underway. This study analyzed characteristics of TQI values evaluating track irregularity, investigated the relationship between crack progress and TQI, and then evaluated the correlation between the two values. Through our analysis, we found that there is a need to supplement the problems of the current method and develop a track evaluation index which takes cracking into account. We also concluded that TQI is the main decision-making tool in track maintenance.