Browsing by Author "Chiou, HK"

Now showing 1 - 6 of 6

An extended approach of multicriteria optimization for MODM problems
(2003)
Chiou, HK
;
Tzeng, GH
;
科技管理研究所
;
Institute of Management of Technology
In this paper we propose an extended method for multicriteria optimization and compromise solution to solve multiple objective decision making (MODM) problems. This method assumes that optimal compromise solution should have the shortest distance from the positive ideal solution (PIS) as well as the longest distance from the negative ideal solution (NIS). We use the membership function of fuzzy set theory to express the satisfaction level, and use max-min operation for this bi-objective programming problem To illustrate this procedure, prequalification for the project bidding process of an outsourcing partner for semiconductor enterprise in Taiwan is solved by use of our procedure.
Evaluating sustainable fishing development strategies using fuzzy MCDM approach
(2005-06-01)
Chiou, HK
;
Tzeng, GH
;
Cheng, DC
;
科技管理研究所
;
Institute of Management of Technology
In actual environmental investment for industry, the stakeholders are often required to evaluate the investment strategies according to their own subjective preferences in terms of numerical values from various criteria, such as economic effectiveness, technique feasibility and environmental regulation. Thus, this situation can be regarded as a fuzzy multiple criteria decision-making (MCDM) problem, so the fuzziness and uncertainty of subjective perception should be considered. This paper proposes an alternative approach, the non-additive fuzzy integral, to cope with evaluation of fuzzy MCDM problems particularly while there is dependence among considered criteria. To illustrate the proposed procedure, the sustainable development strategy for aquatic product processors in Taiwan is investigated. In this paper we employ triangular fuzzy numbers to represent the decision makers' subjective preferences on the considered criteria, as well as for the criteria measurements to evaluate a sustainable development planning case for industry. Firstly, in this study we employ factor analysis to extract four independent common factors from those criteria. Secondly, we construct the evaluation frame using AHP composed of the above four common factors with twelve evaluated criteria, and then derive the relative weights with respect to considered criteria. Thirdly, the synthetic utility value corresponding to each sustainable development strategy is aggregated by the fuzzy weights with fuzzy performance values, and the best investment strategies can then be decided. Through this study, we successfully demonstrate that the non-additive fuzzy integral is an effective evaluation and appears to be more appropriate than the traditional simple additive weighted method, especially when the criteria are dependent. (c) 2004 Elsevier Ltd. All rights reserved.
Fuzzy C-means clustering for the optimal portfolio of machinery industrial sustainable development strategies in Taiwan
(2004)
Chiou, HK
;
Tzeng, GH
;
Yuan, BJC
;
Wang, CP
;
科技管理研究所
Many products of machinery industry that produced in Taiwan ranked within top-ten exports Countries around the world. However, with the dynamic change in both the internal and external environment, production volume, imports and exports dropped simultaneously in 2001. In order to strengthen the industry's competitive advantage, we propose ten Sustainable strategies for machinery industry through focus opinions and employ fuzzy hierarchical analysis approach to find the order these strategies. Furthermore, we introduce fuzzy c-means Clustering to determine the optimal combination of these strategies for sustainable development. Finally, three clusters be extracted for enhancing the industrial promotion, improving national competitiveness and sustainable development, Through this research, we successfully demonstrate that fuzzy C-means clustering not only provides good discriminating power in pattern recognition, but also contribute to good portfolio selection for industry.
Fuzzy multiple-criteria decision-making approach for industrial green engineering
(2002-12-01)
Chiou, HK
;
Tzeng, GH
;
運輸與物流管理系註：原交通所+運管所
;
科技管理研究所
;
Department of Transportation and Logistics Management
This paper describes a fuzzy hierarchical analytic approach to determine the weighting of subjective judgments. In addition, it presents a nonadditive fuzzy integral technique to evaluate a green engineering industry case as a fuzzy multicriteria decision-making (FMCDM) problem. When the investment strategies are evaluated from various aspects, such as economic effectiveness, technical feasibility, and environmental regulation, it can be regarded as an FMCDM problem. Since stakeholders cannot clearly estimate each considered criterion in terms of numerical values for the anticipated alternatives/strategies, fuzziness is considered to be applicable. Consequently, this paper uses triangular fuzzy numbers to establish weights and anticipated achievement values. By ranking fuzzy weights and fuzzy synthetic utility values, we can determine the relative importance of criteria and decide the best strategies. This paper applies what is called a X fuzzy measure and nonadditive fuzzy integral technique to evaluate the synthetic performance of green engineering strategies for aquatic products processors in Taiwan. In addition, we demonstrate that the nonadditive fuzzy integral is an effective evaluation and appears to be appropriate, especially when the criteria are not independent.
Grey prediction model for forfcasting the planning material of equipment spare parts in navy of Taiwan
(2004)
Chiou, HK
;
Tzeng, GH
;
Cheng, CK
;
Liu, GS
;
科技管理研究所
The inventory management of maintenance spare pails plays all important role on their logistic policy. However, for the reasons of insufficient data or uncertain demand of maintenance requirement that we have, the traditional forecasting method is generally hard to predict the optimal quantity of spare parts fitting the requirement. In this Study, we introduce Grey Prediction Model (GPM) to coping with such problem. After taking three types weapon system periodic items of planning material from 1999 to 2002, we then apply GM(1,1) model to predict the planning requirement of intermittent spare parts of 2003. In order to verify the performance of our forecasting model, we also compare the results With the observed data which are calculated by the rule of technical manual of equipments. Through this Study, we demonstrate that the GM(1,1) conduct a good accuracy on prediction of spare pails especially in Sialations of insufficient data, which accurate prediction should reduce the operation cost and improve the reliability of maintenance equipment.
Idea with FMOP method for evaluating the performance of R&D projects in Taiwan
(2004)
Tzeng, GH
;
Chiou, HK
;
Tang, WH
;
科技管理研究所
;
Institute of Management of Technology
In this paper, we proposed all alternative approach for dealing with imprecise data ill Data Envelopment Analysis. First, we transfer the evaluated data to upper and lower bounds for performance estimation. Second, utilizing fuzzy multiple objective programming method estimate the relative efficiency score of decision making units (DMU). The proposed approach adopted to improve the discriminating power of DEA with imprecise data. The performances of government funded R&D projects in Taiwan applied to illustrate the merit of our approach. Finally, we categorize the performance of twenty technology applications called DMU in three clusters, four are absolutely efficient, eleven are weak efficient and five are inefficient.