Intelligent Decision-Making on Modular Products Using Fuzzy Algorithms

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Abstract:

In daily life, it is unavoidable to make a lot of different decisions. Unfortunately, people are not optimal decision makers and do not act rationally when selecting the desired product [1]. To help people select the “right” product to meet their needs, a customizable model based on the fuzzy algorithms is proposed in this study. The linguistic triangular fuzzy variables are used to quantify the judgment intensities to establish the customizable model. The relationship between individual’s needs and product alternatives are constructed by using the fuzzy inference and fuzzy distance algorithms. With the program created in this research, the user will be able to customize the product and obtain the suggested combination of alternatives that fits the user’s needs by selecting the required linguistic terms. A bicycle is chosen as the objective product for a case study in this research and this proposed model can also be used with other products.

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3686-3690

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January 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] M.S. Sanders and E.J. McCormick: Human Factors in Engineering and Design (McGraw-Hill, New York 1993).

Google Scholar

[2] N.A. Zadeh: Information and Control Vol. 8 (1965), p.338.

Google Scholar

[3] C.H. Hsieh and S.H. Chen: Information Sciences Vol. 121 (1999), p.61.

Google Scholar

[4] C.T. Chen: Fuzzy Sets and Systems Vol. 118 (2001), p.65.

Google Scholar

[5] J. Sun, D.K. Kalenchuk, D. Xue and P. Gu: Robotics and Computer Integrated Manufacturing Vol. 16 (2000), p.383.

Google Scholar

[6] O. Kulak: Expert Systems with Applications Vol. 29 (2005), p.310.

Google Scholar

[7] O. Kulak and C. Kahraman: Information Sciences Vol. 170 (2005), p.191.

Google Scholar

[8] D. Dubois and H. Prade: International Journal of System Science Vol. 9 (1978), p.613.

Google Scholar

[9] S. Heilpern: Fuzzy Sets and Systems Vol. 91 (1997), p.259.

Google Scholar