یک رویکرد جدید به حل برنامه‌ریزی خطی تماماً فازی با اعداد ذوزنقه‌ای با استفاده از توابع تبدیل
محورهای موضوعی : آمار
1 - دانشکده علوم ریاضی، دانشگاه مازندران، بابلسر، ایران
کلید واژه: Conversion function, Fully fuzzy linear programming, Multi-objective linear program, Trapezoidal and triangular fuz,
چکیده مقاله :
در این مقاله ما یک مدل شبکه عصبی برای تشخیص واحدهای تصمیمگیرنده کارا در تحلیل پوششی دادهها معرفی میکنیم. مدل شبکه عصبی پیشنهادی از یک مسئله بهینهسازی نامقید حاصل میشود. از دیدگاه تئوری نشان داده میشود شبکه عصبی پیشنهادی دارای پایداری لیاپانف و همگرای سراسری میباشد. مدل پیشنهادی تک لایه میباشد. شبیه سازی نشان میدهد مدل پیشنهادی قادر به تشخیص واحدهای کارا در تحلیل پوششی دادهها میباشد.
Recently, fuzzy linear programming problems have been considered by many. In the literature of fuzzy linear programming several models are offered and therefore some various methods have been suggested to solve these problems. One of the most important of these problems that recently has been considered; are Fully Fuzzy Linear Programming (FFLP), which all coefficients and variables of the problem are the same kind of fuzzy numbers. One of most common of them is the model in which all fuzzy parameters are discussed by triangle numbers. In this paper, we first define a fully fuzzy linear programming with trapezoidal numbers and then suggest a new method based on reducing the original problem to the problem with triangle number. Specially, a conversion function for converting two trapezoidal and triangular numbers to each other is offered. Finally, the mentioned method is illustrated by a numerical example.
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