Parametric approach for approximate efficiency of robust multiobjective fractional programming problems

2021 ◽  
Author(s):  
Tadeusz Antczak
Keyword(s):  
Fractional Programming ◽  
Parametric Approach ◽  
Multiobjective Fractional Programming

APPROXIMATE EFFICIENCY FOR n-SET MULTIOBJECTIVE FRACTIONAL PROGRAMMING

2004 ◽  
Vol 21 (02) ◽  
pp. 197-206 ◽  
Author(s):  
NARENDER KUMAR ◽  
R. K. BUDHRAJA ◽  
APARNA MEHRA
Keyword(s):  
Fractional Programming ◽  
Sufficient Conditions ◽  
Approximate Solutions ◽  
Efficient Solutions ◽  
Parametric Approach ◽  
Multiobjective Fractional Programming ◽  
Set Functions ◽  
New Concepts ◽  
Multiobjective Fractional Programming Problem ◽  
Necessary And Sufficient

In this paper, we introduce new concepts of ε-weak efficient solutions and ε-efficient solutions for a nonconvex multiobjective fractional programming problem involving n-set functions. Using an ε-parametric approach and a new theorem of alternative for nonconvex n-set functions, some necessary and sufficient conditions for ε-approximate solutions are derived

scholarly journals Symmetric dual multiobjective fractional programming

1991 ◽  
Vol 50 (1) ◽  
pp. 67-74 ◽  
Author(s):  
T. Weir
Keyword(s):  
Fractional Programming ◽  
Multiobjective Fractional Programming ◽  
Duality Theorems

AbstractA pair of symmetric dual multiobjective fractional programming problems is formulated and appropriate duality theorems are established.

Iterative Parametric Approach for Quadratically Constrained Bi-Level Multiobjective Quadratic Fractional Programming

2020 ◽  
Vol 17 (11) ◽  
pp. 5046-5051
Author(s):  
Vandana Goyal ◽  
Namrata Rani ◽  
Deepak Gupta
Keyword(s):  
Fractional Programming ◽  
Optimization Problem ◽  
Programming Model ◽  
Pareto Optimal Solutions ◽  
Parametric Approach ◽  
Second Stage ◽  
Quadratic Fractional Programming ◽  
Upper Level ◽  
Quadratically Constrained ◽  
Constraint Method

The paper proposed an iterative parametric approach procedure for solving Bi-level Multiobjective Quadratic Fractional Programming model. The Model is divided into two levels-upper and lower. In the first stage of the approach, a set of pareto optimal solutions of upper Level is obtained by converting the problem into equivalent single non-fractional parametric objective optimization problem by using parametric vector and ε-constraint method. Then for the second stage, the solution of upper level is followed by the lower level decision maker while finding solution with the proposed algorithm to obtain the best preferred solution. A numerical example is solved in the last to validate the feasibility of the approach.

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