An improved fuzzy synthetic evaluation using expanded optimization algorithm for combining index weights

Fuzzy synthetic evaluation is usually be influenced significantly by the matrix of fuzzy relation and index vector. For a sequential segmentation category, the principle of the lowest cost, the principle of maximum degree of measure and the principle of maximum degree of membership sometimes can get unreasonable conclusion, even sometimes can get error conclusion, because they conceal the difference of two degree of membership. First of all, a new expanded optimization algorithm is presented for combining index weights, then bring out a improved fuzzy synthetic evaluation method based on reliability code. The proposed method can overcome the shortages of the traditional fuzzy synthetic evaluation. Case results clearly show that the proposed method is attractive and effective.