On product classification with various membership functions and binary behaviour

Abstract

This study proposes a fuzzy programming method for Internet product classification in which many realistic membership functions (ie, increasing, decreasing, triangular and piecewise linear functions) are used for easy classification. A new concept—binary behaviour—is introduced to represent the product classification problem involving the achievement of fuzzy goals, some of which are achieved and some of which are not. That is, some attributes dominate other attributes that are often found in real problems. In addition, achievement functions are provided to solve a multi-objective decision-making problem in which the utility values are increased as much as possible, to suit real-world situations. Finally, to demonstrate the usefulness of the proposed methods, numerical examples are also included.

Keywords:

• fuzzy clustering
• product classification
• binary behaviour

Acknowledgements

The author thanks the anonymous referees for their valuable suggestions which improved the presentation of the paper.