Browsing by Author "Ko, Yu-Chien"

Now showing 1 - 5 of 5

A note on "Reducing the number of binary variables in cutting stock problems"
(2014-02-01)
Lu, Hao-Chun
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Ko, Yu-Chien
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Huang, Yao-Huei
;
資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
This study proposes a deterministic model to solve the two-dimensional cutting stock problem (2DCSP) using a much smaller number of binary variables and thereby reducing the complexity of 2DCSP. Expressing a 2DCSP with stocks and cutting rectangles requires binary variables in the traditional model. In contrast, the proposed model uses binary variables to express the 2DCSP. Experimental results showed that the proposed model is more efficient than the existing model.
A simple utility function with the rules-verified weights for analyzing the top competitiveness of WCY 2012
(2014-03-01)
Ko, Yu-Chien
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Fujita, Hamido
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Tzeng, Gwo-Hshiung
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科技管理研究所
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Institute of Management of Technology
Uncertainty always causes hesitations during decision-making. The uncertainty reduction however is not available through simple operations and easy interpretation. This research solves this problem by proposing an evidential weight based on preferences (EWP). The key technique of EWP is the integration of the roughness measures of an induction rule to reduce noises in doubts. The utilities composed of the derived weight from EWP are empirically used on World Competitiveness Yearbook 2012 to analyze the benchmarking nations. This case study shows European welfare nations (Denmark, Finland, Norway, and Sweden) focus on the long term strategic competitiveness while Asian tiger nations (Singapore, Hong Kong, Korea, and Taiwan) are energetic on short term surviving competitiveness. (C) 2013 Elsevier B.V. All rights reserved.
An extended fuzzy measure on competitiveness correlation based on WCY 2011
(2013-01-01)
Ko, Yu-Chien
;
Fujita, Hamido
;
Tzeng, Gwo-Hshiung
;
科技管理研究所
;
Institute of Management of Technology
The fuzzy measure can highlight important information in analyzing component features, patterns, and trends. However, fuzzy densities and interaction effects are usually unknown or uncertain for implications thus making the fuzzy measure limited in applications. This research proposes an extended fuzzy measure to derive the conditional fuzzy densities from dominance-based rough set approach (DRSA), multiply preferences and the derived densities into utilities, fulfill fuzzy measure identification, and empower the fuzzy measure to aggregate utilities. For illustration, the extended fuzzy measure is applied on World Competitiveness Yearbook 2011 to imply policy-making information for Greece, Italy, Portugal, and Spain. (C) 2012 Elsevier B.V. All rights reserved.
An Optimal Classification Method for Biological and Medical Data
(2012)
Huang, Yao-Huei
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Ko, Yu-Chien
;
Lu, Hao-Chun
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
This paper proposes a union of hyperspheres by the mixed-integer nonlinear program to classify biological and medical datasets. A classifying program with nonlinear terms uses piecewise linearization technique to obtain a global optimum. The numerical examples illustrate that the proposed method can obtain the global optimum more effectively than current methods.
INDUCING DYNAMIC RULES OF NATIONS' COMPETITIVENESS FROM 2001-2005 MCI-WCY
(2009-09-01)
Li, Han-Lin
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Ko, Yu-Chien
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
A nation's competitiveness has become more and more important in forming government strategy and business decision making. This study proposes an optimization model, instead of regression model or neural network model, to induce rules for dynamic nations' competitiveness based on the Major Competitiveness Indicators of the World Competitiveness Yearbook. Fourteen attributes are used to form the dynamic rules expressed in "IF... THEN..." forms. According to the induced rules, the strategic implications are suggested for various groups of nations to improve or to sustain their competitiveness.