Hua-Kai Chiou

An Extended Approach of Multicriteria Optimization for MODM Problems

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.

Multiple Objective Compromise Optimization Method to Analyze the Strategies of Nanotechnology in Taiwan

Analytic Hierarchy Process (AHP) is a popular technique often used to model subjective decision-making processes based on multiple attributes; Hwang and Yoon (1981) originally proposed TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach to solve multiple attribute decision-making problems using the concept of optimal compromise solution. Lai et al. (1994) further utilized the Euclidean distance concept to drive the TOPSIS approach for MODM problems. In this research, we introduced a compromise optimization method, integrating AHP with TOPSIS, to evaluate the development strategies of nanotechnology for enhancing the global position of Taiwan. Firstly, fuzzy hierarchy analytic process was used to derive the relative weights of the considered criteria from participated evaluators, and then the synthetic value were aggregated by criteria weights with performance score which assigned by participant’s subjective judgment. This proposed method assumes that the optimal solution should have the shortest distance from the positive ideal solution as well as the farthest distance from the negative ideal solution. We apply this method to evaluate the synergy among proposed strategies for industrialized nanotechnology.

Correspondence Analysis to Screening the Implementation of One Village One Product Programs in Taiwan

One Village One Product (OVOP) programs are a community-centered and demand-driven for local economic development approach initiated by Oita Prefecture in Japan in the 1970s. The uniqueness of these programs are those they intended to achieve the regional economic development through adding value to products employing locally available resources through processing, quality control and marketing. The objectives of OVOP programs in Taiwan are supported by government to promoting the economic development and cooperative relationship of each country and region through the localization and innovation. Firstly, we employ Delphi process to converge eighteen critical criteria with respect to three key dimensions for evaluation. We then utilize graphical correspondence analysis to exploring the implementation of OVOP programs and conduct some meaningful suggestions of the policy direction from these empirical cases. Through this study we successfully demonstrate that correspondence analysis is an efficiency technique for industrial analysis and strategy management in real world.

Applying Multiobjective Compromise Approach to Exploring the Strategic Plan of Fuel Cell Technology

The fuel cell is one of the most important energy products in the 21st century, and most industrial-advanced countries in the world are placing high expectation on its development. The applications of fuel cells in Taiwan has spread broadly in many products and it takes high global market share, such as notebook computers, PDAs and digital cameras, along with items like automobiles, motorcycles and power generation equipment. In this study we introduce a multi-objective compromise optimization to solve the optimal strategic plans of fuel cell industry, which is emerging industry in Taiwan. In the first step, we introduce popular analytic hierarchy process with fuzzy set theory to establish the hierarchy system to determine the relative importance of evaluated criteria. Secondly, fuzzy geometric mean method was utilized to aggregate the performance score by individual judgment of evaluator, which scores express the measurement of strategic plan proposed by participated experts. Thirdly, the synthetic value of each strategic plan was integrated by criteria weights with performance score, and positive ideal solution (PIS) and negative ideal solution (NIS) were defined by Minkowskis distance metric function. Fourthly, the optimal compromise solution will be derived which should have the shortest distance from the positive ideal solution as well as the farthest distance from the negative ideal solution. Along with the results of this research, we successfully demonstrate that the multi-objective compromise optimization is a good alternative for evaluation of multiple criteria decision making problems

Fuzzy multiple ibjective programming for performance evaluation of public sectors in Taiwan

The traditional data envelopment analysis model so called CCR model proposed by Charnes et al.(1978), which model evaluates the relative efficiency of each decision making unit with multiple input and multiple output variables. However, there are two reasons make the CCR model weak discriminative power. One is impractical weights of decision variables; the other is the insufficient number of decision making units. Chiang and Tzeng (2000) introduced fuzzy multiple objective programming (FMOP) to improve the discriminative power of evaluating model This FMOP model derived the common weights for all decision making units and improved the problem of discrimination in CCR model. In this study, we applied these evaluation models to derive the efficiency score of the Accounting & Statistics Departments of Air Force in Taiwan. We also compared the results of these models and then summarized some research findings in the end of this paper, it might provides some useful implications for improving the competition of decision making units, which is one of the most important factors of modern war.