A new parametric method for ranking fuzzy numbers based on positive and negative ideal solutions

رتبه بندي اعداد فازي نقش بسيار مهمي در واحد هاي تصمي گيري و روشهاي بهينه سازي ايفا مي كند. قبل از اينكه عملي روي يك عدد فازي صورت گيرد بايستي رتبه بندي گردد. هدف از اين مقاله ارايه يك روش جديد براي رتبه بندي اعداد فازي تعميم يافته مي باشد. روش ارايه شده بر مبناي فاصله موجود بين جوابهاي ايده ال مثبت و جوابهاي ايده ال منفي مي باشد. مزيت اصلي روش آنست كه اعداد فازي تعميم يافته را به درستي رتبه بندي كرده و با مسايل روز مره نيز سازگاري بسيار داشته و محاسبات ساده تري دارد. اشكالات اساسي موجود در ساير روشها نيز پوشش داده مي شود.

Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. The main aim of this paper is to propose a new approach for the ranking of generalized fuzzy numbers. The proposed ranking approach is based on distance between positive ideal solution and negative ideal solution. The main advantage of the proposed approach is that it provides the correct ordering of generalized and normal fuzzy numbers and it is very simple and easy to apply in the real life problems. The approach is illustrated by numerical examples, showing that it overcomes several shortcomings such as the indiscriminative and counterintuitive behavior of existing fuzzy ranking approaches.