أعضاء هيئة التدريس - جامعة بنها
A novel algorithm for generating Pareto frontier of bi-level multi-objective rough nonlinear programming problem
Ain Shams Engineering Journal • 2021
معلومات البحث
المؤلفون
M.A. Elsisy, M.A. El Sayed, & Y. Abo-Elnaga
الكلمات المفتاحية
Multi-objective programming
Bi-level programming
Rough set
KKT optimality
المجلة العلمية
Ain Shams Engineering Journal
الناشر
Elsevier
المجلد
in press
العدد
Not Available
الصفحات
Not Available
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
This paper discusses a new algorithm for generating the Pareto frontier for bi-level multi-objective rough
nonlinear programming problem (BL-MRNPP). In this algorithm, the uncertainty exists in constraints
which are modeled as a rough set. Initially, BL-MRNPP is transformed into four deterministic models.
The weighted method and the Karush-Kuhn-Tucker optimality condition are combined to obtain the
Pareto front of each model. The nature of the problem solutions is characterized according to newly proposed
definitions. The location of efficient solutions depending on the lower/upper approximation set is
discussed. The aim of the proposed solution procedure for the BL-MRNPP is to avoid solving four problems.
A numerical example is solved to indicate the applicability of the proposed algorithm.
nonlinear programming problem (BL-MRNPP). In this algorithm, the uncertainty exists in constraints
which are modeled as a rough set. Initially, BL-MRNPP is transformed into four deterministic models.
The weighted method and the Karush-Kuhn-Tucker optimality condition are combined to obtain the
Pareto front of each model. The nature of the problem solutions is characterized according to newly proposed
definitions. The location of efficient solutions depending on the lower/upper approximation set is
discussed. The aim of the proposed solution procedure for the BL-MRNPP is to avoid solving four problems.
A numerical example is solved to indicate the applicability of the proposed algorithm.