• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.493-498
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• 2013

This paper is aimed to priority evaluation of preliminary cases for IMO -IMS(International Maritime Organization- Information Management System) using fuzzy TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) and AHP(Analytic Hierarchy Process). To this solve, therefore, this paper extract 24 preliminary cases and select 4 major preliminary alternative cases after analysing the structure of its alternative cases using FSM(Fuzzy Structure Modeling). Also, the weights of evaluation factors determine using AHP which able to keep the consistency when decision-makers assess. In AHP method, but, the numbers of paired comparison incerase as much as the numbers of the comparison items increase and because this evaluation have the many of vagueness, the decision of final ranking is used to fuzzy TOPSIS method which is included TOPSIS and Fuzzy Set Theory. The result are developed as order as Management of IMO Convention Information, Delivery of IMO Convention Information, Total IMO Database, Knowledge Hub of IMO Convention Information in IMO-IMS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.917-926
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• 2013

This study presents the feasibility of fuzzy multi-criteria decision making (MCDM) techniques for the robust prioritization of projects. It is applied to water resources planning problem. Results from weighted sum method (WSM), analytic hierarchy process (AHP), revised analytic hierarchy process (R-AHP), and TOPSIS are compared with those from Fuzzy WSM, Fuzzy, AHP, Fuzzy R-AHP, and Fuzzy TOPSIS. For the calculation, all weights on criteria and the normalized data were obtained from the same investigation. As a result, the rankings from four MCDM techniques are slightly different while those from fuzzy MCDM show the comparatively consistent ranking. Therefore, it is desirable to use fuzzy MCDM technique when MCDM is used for the prioritization problem, since fuzzy MCDM can include the uncertain variability of input data and weighting values on criteria.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.231-240
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• 2018

Automobile industry is facing a variety of risks, including the rise of international oil price and the increase of car prices. In addition to the government's deregulation, efforts should be made to improve management aiming at higher production efficiency. In this study, we established a model for evaluating the procurement logistics based on the Fuzzy-AHP-TOPSIS by using the factors that are actually used in real companies aimed at the improvement of procurement logistics. A total of three automobile factories of Company G were chosen as the evaluation subject. In the result of the Fuzzy-AHP analysis that was conducted on a sample of three car factories, solving the long-term quality problems, minimizing the stop time due to the shortage of materials, preventing the of equipment accident, and solving the short-term quality problems were proven to be the most important factors. TOPSIS analysis result indicated that Factory B had the best procurement logistics. Our study has significance that it can contribute to the improvement of efficiency in the automobile industry as the evaluation model suggested in this study can be used for regular evaluation related to the procurement logistics in the future.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.51-68
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• 2017

Financial technology (FinTech) is an emerging financial service sector include innovations in financial literacy and investment, retail banking, education, and crypto-currencies like bitcoin. One of the crucial branch of financial technology-third-party payment (TPP) is undergoing rapid growth, with online/mobile systems replacing offline financial systems. System quality and user attitudes are key perceptions driving third-party payment usage, the importance of these perceptions, however, may be different with countries as users' thinking varies from country to country. Thus, the purpose of this study is to elaborate how factors differ from China to Korea by drawing on the unified theory of acceptance and use of technology (UTAUT2). Additionally, this study also aims to propose a multi-attribute evaluation of the third-party online payment system based on analytic hierarchy process (AHP), fuzzy sets and technique for order performance by similarity to ideal solution (TOPSIS), to examine the relative importance of the perceptions influencing new technology adoption intention. The results showed that the price value has the most significant influence on Chinese perceptions, while the perceived credibility has the most significant effect on Korean perceptions. Sub-criteria also performs different results to Chinese and Korean third-party online payment system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• 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.

• 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 Korea Port Economic Association
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• v.37 no.4
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• pp.13-31
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• 2021

Since the signing of the Korea-Europe Free Trade Agreement, the volume of trade transactions between South Korea and Europe has increased. The traditional single-mode transport system has been transformed into an intermodal transport system using two or more modes of transport. In addition, the conventional sea and air transport routes have been restricted, leading to a decline in Korean exports to Europe, and the rail transport mode is becoming mainstream in the market due to the influence of COVID-19. This paper focuses on the China-Railway Express to explore a new intermodal transport route from Korea to Europe. First, the fuzzy analytic hierarchy process (AHP) is used to evaluate the factor weights when selecting intermodal transport routes from Korea to Europe. Then, the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is used to rank three alternatives. The results show that among the four factors (total cost, total time, transportation capability, and service reliability), the total cost is the most significant factor, followed by the total time, service reliability, and transportation capability. Furthermore, the alternative route 1 (Incheon-Dalian-Manchuria-Hamburg) is preferred.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.149-159
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• 2019

Six sigma is an innovative management movement which provides improved business process by adapting the paradigm and the trend of market and customers. Suitable selection of six sigma project could highly reduce the costs, improve the quality, and enhance the customer satisfaction. There are existing studies on the selection of Six Sigma projects, but few studies have been conducted to select the correct project under an incomplete information environment. The purpose of this study is to propose the application of integrated MCDM techniques for correct project selection under incomplete information. The project selection process of six sigma involves four steps as follows: 1) determination of project selection criteria 2) calculation of relative importance of team member's competencies 3) assessment with project preference scale 4) finalization of ranking the projects. This study proposes the combination methods by applying group fuzzy Analytical Hierarchy Process (AHP), an easy defuzzified number of Trapezoidal Fuzzy Number (TrFN) and Grey Relational Analysis (GRA). Both of the weight of project selection criteria and the relative importance of team member's competencies can be evaluated by group fuzzy AHP. Project preferences are assessed by easy defuzzified scale of TrFN in case of incomplete information.)