Improved TOPSIS Methods for Multi-Response Optimization

To find the optimal combination of parameters in product or process design, there are always more than one response needed to be optimized simultaneously, which is called as optimization of multi-response problems. TOPSIS (technique for order preference by similarity to ideal solution) method, as a multiple attribute decision making (MADM) methodology, is often used for solving problems with multivariate quality characteristics. In conventional TOPSIS method, responses are usually transformed into loss of quality, and then normalized by the largest quality loss. Based on the conventional TOPSIS method, two improved methods are proposed and illustrated by an example from literature, the two methods gain similar value from optimization, and the result indicates their reasonableness and effectiveness.