This study proposes a multi-attribute decision making based approach for product design concept evaluation and selection. The technique for order preference by similarity to ideal solution (TOPSIS) is combined with fuzzy sets and information entropy. While the fuzzy sets theory is employed to capture the associated vagueness in the expert judgment, the combination of information entropy method with multi-attribute decision making makes the approach computationally efficient. We present the results of the evaluation of design concepts which demonstrate the feasibility and practicability of the approach. The proposed approach will result in considerable time and cost saving by identifying the most promising product design concepts and short-listing for further design and development activities.
