Open AccessNondifferentiable generalized minimax fractional programming under (Ф,ρ)-invexity
Author(s) -
Balendu Bhooshan Upadhyay,
Tadeusz Antczak,
Shashi Kant Mishra,
K. K. Shukla
Publication year - 2022
Publication title -
yugoslav journal of operations research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.221
H-Index - 21
eISSN - 1820-743X
pISSN - 0354-0243
DOI - 10.2298/yjor200915018u
Subject(s) - minimax , mathematics , fractional programming , duality (order theory) , class (philosophy) , mathematical optimization , dual (grammatical number) , computer science , nonlinear programming , combinatorics , artificial intelligence , nonlinear system , art , physics , literature , quantum mechanics
In this paper, a class of nonconvex nondifferentiable generalized minimax fractional programming problems is considered. Sufficient optimality conditions for the considered nondifferentiable generalized minimax fractional programming problem are established under the concept of (?,?)-invexity. Further, two types of dual models are formulated and various duality theorems relating to the primal minimax fractional programming problem and dual problems are established. The results established in the paper generalize and extend several known results in the literature to a wider class of nondifferentiable minimax fractional programming problems. To the best of our knowledge, these results have not been established till now.