• Industrial Engineering and Management Systems
• /
• v.9 no.2
• /
• pp.88-96
• /
• 2010

This paper presents a two-phase quantitative framework to aid the decision making process for effective selection of an efficient freight logistics hub from 8 alternatives in Thailand on the North-South economic corridor. Phase 1 employs both multiple regression and Pearson Feature selection to find the important criteria, as defined by logistics hub score, and to reduce number of criteria by eliminating the less important criteria. The result of Pearson Feature selection indicated that only 5 of 15 criteria affected the logistics hub score. Moreover, Genetic Algorithm (GA) was constructed from original 15 criteria data set to find the relationship between logistics criteria and freight logistics hub score. As a result, the statistical tools are provided the same 5 important criteria, affecting logistics hub score from GA, and data mining tool. Phase 2 performs the fuzzy stochastic AHP analysis with the five important criteria. This approach could help to gain insight into how the imprecision in judgment ratios may affect their alternatives toward the best solution and how the best alternative may be identified with certain confidence. The main objective of the paper is to find the best alternative for selecting freight logistics hub under proper criteria. The experimental results show that by using this approach, Chiang Mai province is the best place with the confidence interval 95%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.352-357
• /
• 1998

Conventional marketing research generally focuses on a single layer's benefit. A notable example is the consumer layer providing managers with partial market information to evaluate relevant strategies. As generally known, marketing management encounters complex supply and demand behaviors, thereby necessitation that a successful marketing strategy adopt multi-layer considerations, such as the consumer layer, channel-retailer layer, and marketing planner layer. In light of above situation, this study applies fuzzy theory and the analytic hierarchy process(AHP) technique to analyze the performances of marketing strategies under multi-layer benefits, In addition, conventional marketing research has difficulty in efficiently allocating the limited budget so that each desired criterion can be significantly enhanced by a group of events. Therefore, a weighting structure among the goal, layers, criteria, and strategies(i.e. a group of events) is also developed herein to trace the influential process and assist marketing managers in efficiently allocating resources(i.e.budget).

• Journal of Korean Society for Quality Management
• /
• v.38 no.1
• /
• pp.85-95
• /
• 2010

In this paper we propose a product-service valuation model which is usable as a decision-making tool in order to attain a competitive advantage in service in the manufacturing industry. With this purpose, service quality, product quality and costs as valuation criteria are selected. Also, the paper utilizes an AHP model in order to differentiate a fuzzy theory and valuation factors to ensure objectivity in the evaluated results while excluding subjective factors in conducting the product-service valuation. Accordingly, the product-service valuation model and valuated results proposed in this paper are expected to be useful as a basic data for decision-making in order to draw competitive advantage strategies of service in the manufacturing industry.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2006.11a
• /
• pp.236-242
• /
• 2006

세계적으로 각 분야에서 SERVQUAL 모형과 SERVPERF 모형 등을 이용한 서비스품질에 대한 측정과 관련된 연구들이 많이 수행되어 오고 있지만 서비스품질을 계량화시키기 위한 연구는 활성화되고 있지 못하는 상황이다. 따라서, 본 연구의 목적은 불확실하고 주관적인 환경에서 서비스품질을 객관성있게 측정하고 계량화시키기 위해서 L.A. Zadeh가 제안한 퍼지이론의 Triangular Fuzzy Number(TFN) 와 T.L. Saaty가 제안한 Analytic Hierarchy Process (AHP)를 이용하여 서비스품질을 측정하기 위한 방법을 제안하는 것이고, 본 연구를 통해서 조직의 제한적 자원으로 고객만족 극대화를 실현하기 위한 경쟁우위적 전략의 일환으로써 서비스품질을 제고시키는데 효율적이며 효과적인 의사결정안이 도출될 것으로 사료된다.

• Journal of the military operations research society of Korea
• /
• v.26 no.2
• /
• pp.55-74
• /
• 2000

A knowledge-based with production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a method to reflect the dynamic nature of a system when we make inferences with a knowledge-based system. This paper suggests a strategy of dynamic inference that can be used to take into account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy production rules. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by the AHP(Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected in an inference with fuzzy production systems.

• Industrial Engineering and Management Systems
• /
• v.7 no.1
• /
• pp.34-43
• /
• 2008

In recent years, many electronics producing firms have looked upon total quality management (TQM) strategy as a means by which they could maintain competitive advantage. This empirical research evaluates TQM strategic factors in order to determine the critical success factors in environmental uncertainty. Fuzzy analytic hierarchy process (FAHP) is the proposed research methodology to discuss and tackle the different decision criteria like effective leadership, people management, customer focus, strategic plan and process management, being involved in identifying the TQM strategic critical success factors with uncertainty. The result shows that effective leadership is the most critical success factor in TQM strategy.

• Journal of Korea Water Resources Association
• /
• v.46 no.2
• /
• pp.171-182
• /
• 2013

This paper presents the application of fuzzy set theory in multi criteria decision making (MCDM). FAHP (Fuzzy Analytic Hierarchy Process) method was used to rank alternatives to find the most reasonable and efficient way of agricultural reservoir water resources assessment. 6 criteria and 10 subcriteria had been identified and compared to secure agricultural water resources. Fuzzy numbers and linguistic variables were presented to address inherently uncertain or imprecise data. Comparison analysis of decision making method was also carried out to find a way of suitable decision making and validity of FAHP was discussed.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.8 no.4
• /
• pp.344-359
• /
• 2016

Due to the increasing occurrence of maritime accidents and high-level requirements and modernization of naval wars, the concept of ship environment adaptability becomes more and more important. Therefore, it is of great importance to carry out an evaluation system for ship environment adaptability, which contributes to both ship design and classification. This paper develops a comprehensive evaluation system for ship environment adaptability based on fuzzy mathematics theory. An evaluation index system for ship environment adaptability is elaborately summarized first. Then the analytic hierarchy process (AHP) and entropy weighting methods are applied to aggregate the evaluations of criteria weights for each criterion and the corresponding subcriteria. Next, the multilevel fuzzy comprehensive evaluation method is applied to assess the ship integrative environment adaptability. Finally, in order to verify the proposed approach, an illustrative example for optimization and evaluation of five ship alternatives is adopted. Moreover, the influence of criteria weights, membership functions and fuzzy operators on the results is also analyzed.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.15-22
• /
• 2002

Transportation project appraisal should be precise in order to increase the social welfare and efficiency, and it has been evaluated by only a single criterion analysis such as benefit/cost analysis. However, this method cannot assess some qualitative items, and cannot get a proper solution for the clash of interests among various groups. Therefore, the multi-criteria analysis, which can control these problems, is needed, and then Saaty has developed one of these methods, AHP(Analytic Hierarchy Process) method. In AHP, the project is evaluated through weighted score of the criteria and the alternatives, which is surveyed by a questionnaire of specialists. It is based on some strict suppositions such as reciprocal comparison, homogeneity, expectation, independence relationship between multi-criteria, but supposing that each criterion has independence relation with others is too difficult in two reasons. First, in real situation, there cannot be perfect independence relationship between standards. Second, individuals, even though they are specialists of that area, do not feel the degree of independence relation as same as others. This paper develops a modified AHP method for solving this dependence relationship between multi-criteria. First of all. in this method, the degree of dependence relationship between multi-criteria that the specialist feels is surveyed and included to the weighted score of multi-criteria This study supposes three methods to implement this idea. The first model products the degree of dependence relationship in the first step for calculating the weighted score, and the others adjust the result of weighted score from the basic AHP method to the dependence relationship. One of the second methods distributes the cross weighted score to each standard by constant ratio, and the other splits them using Fuzzy measure such as Bel and Pl. Finally, in order to validate these methods, this paper applies them to evaluate the alternatives which can control public resentments against Korean rail path in a city area.

• Journal of Energy Engineering
• /
• v.16 no.3
• /
• pp.128-148
• /
• 2007

Quality assurance (QA) for nuclear R&D project is very concerned about the poor economy due to the improper selection of QA requirements. This paper proposes a new methodology for determining the relative importance weights of QA requirements considering the attributes of nuclear R&D project. QFD (Quality Function Deployment) is used as a conceptual framework and fuzzy number is introduced to capture the vagueness uncertainty existing in human judgement. Also we use a confidence attitude of decision-maker in order to improve the reliability of extracted attribute level of R&D project. Case study on a nuclear R&D project and scenario analysis are carried out to verify the usefulness and effectiveness of proposed methodology.