أعضاء هيئة التدريس - جامعة بنها
An Interactive Method for Solving Fuzzy Multi-objective Linear Programming Problems
International Journal of Advanced Trends in Computer Science and Engineering • 2022
معلومات البحث
المؤلفون
M. E. Hady Kassem; N. A. El-kholy; M. H. Eid; M. M. Ibrahim
الكلمات المفتاحية
Fuzzy set, interactive method, multi-objective
linear programming.
المجلة العلمية
International Journal of Advanced Trends in Computer Science and Engineering
الناشر
Not Available
المجلد
Vol. 10, No. 4, 2021
العدد
2278-3091
الصفحات
Not Available
publication.type
Local
رابط البحث
Not Available
المواد المرفقة
Not Available
الملخص
This paper is concerned with multi-objective linear
programming problems in which the coefficients are
expressed as fuzzy numbers of triangular type. An interactive
method, to enhance the weights in the weighted sum problem,
is introduced. In the scalarized problem, the weights are
determined via the ideal minimum and maximum values of
the objective functions. A numerical example is given to
clarify the presented method.
This paper is concerned with multi-objective linear
programming problems in which the coefficients are
expressed as fuzzy numbers of triangular type. An interactive
method, to enhance the weights in the weighted sum problem,
is introduced. In the scalarized problem, the weights are
determined via the ideal minimum and maximum values of
the objective functions. A numerical example is given to
clarify the presented method.
programming problems in which the coefficients are
expressed as fuzzy numbers of triangular type. An interactive
method, to enhance the weights in the weighted sum problem,
is introduced. In the scalarized problem, the weights are
determined via the ideal minimum and maximum values of
the objective functions. A numerical example is given to
clarify the presented method.
This paper is concerned with multi-objective linear
programming problems in which the coefficients are
expressed as fuzzy numbers of triangular type. An interactive
method, to enhance the weights in the weighted sum problem,
is introduced. In the scalarized problem, the weights are
determined via the ideal minimum and maximum values of
the objective functions. A numerical example is given to
clarify the presented method.