Fuzzy Logic-based Alternative Searching for Product Customization

H.-C. Tsai, F.-K. Hung, and S.-W. Hsiao (Taiwan)


Customer needs, Fuzzy, Analytic hierarchy process, Artificial intelligence


Many consumers purchase multi-functional products according to their individual preferences. Consumers are normally aware of their basic needs, but often have no idea of product types, functions, usage and terminology showing important information. This research presents a method to translate customer needs into applicable alternative combinations for the products of customers’ desire. In this research, the theory of the analytic hierarchy process (AHP) is utilized to evaluate the importance of customer needs, which are generally rated and described by qualitative expressions. A fuzzy inference model is employed to establish the relationship between customer needs and alternatives for a multi functional product. Then a fuzzy synthetic distance method is used to perform optimal searching for possible alternative combinations in the product. Based on the above-mentioned methods and associated algorithms, a consultative interface is setup for a case study to demonstrate effectiveness.

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