On Constraint Qualifications for Multiobjective Optimization Problems with Vanishing Constraints

2015 ◽  
pp. 95-135 ◽  
Author(s):  
S. K. Mishra ◽  
Vinay Singh ◽  
Vivek Laha ◽  
R. N. Mohapatra
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Constraint Qualifications ◽  
Multiobjective Optimization Problems ◽  
Vanishing Constraints

scholarly journals Strong complementary approximate Karush-Kuhn-Tucker conditions for multiobjective optimization problems

2021 ◽  
pp. 24-24
Author(s):  
Jitendra Maurya ◽  
Shashi Mishra
Keyword(s):  
Multiobjective Optimization ◽  
Optimality Conditions ◽  
Constraint Qualification ◽  
Optimization Problems ◽  
Constraint Qualifications ◽  
Inequality Constraints ◽  
Multiobjective Optimization Problems ◽  
Sequential Optimality Conditions ◽  
Equality And Inequality Constraints ◽  
Optim Theory

In this paper, we establish strong complementary approximate Karush- Kuhn-Tucker (SCAKKT) sequential optimality conditions for multiobjective optimization problems with equality and inequality constraints without any constraint qualifications and introduce a weak constraint qualification which assures the equivalence between SCAKKT and the strong Karush-Kuhn-Tucker (J Optim Theory Appl 80 (3): 483{500, 1994) conditions for multiobjective optimization problems.

scholarly journals First-Order Optimality Conditions in Multiobjective Optimization Problems: Differentiable Case

1970 ◽  
Vol 29 ◽  
pp. 99-105 ◽  
Author(s):  
MM Rizvi ◽  
Muhammad Hanif ◽  
GM Waliullah
Keyword(s):  
Multiobjective Optimization ◽  
Necessary Conditions ◽  
Optimization Problems ◽  
Constraint Qualifications ◽  
Inequality Constraints ◽  
First Order ◽  
Multiobjective Optimization Problems ◽  
Equality And Inequality Constraints ◽  
Vector Valued ◽  
Type Constraint

T. Maeda gave some constraint qualifications to get positive Lagrange multipliers associated with the vector-valued objective function and under these conditions, he derived Karush-Kuhn-Tucker (KKT) type necessary conditions for inequality constraints. In this paper, we have defined these Maeda-type constraint qualifications under different sets and have derived KKT type necessary conditions for both equality and inequality constraints. GANIT J. Bangladesh Math. Soc. (ISSN 1606-3694) 29 (2009) 99-105  DOI: http://dx.doi.org/10.3329/ganit.v29i0.8519

scholarly journals Duality Theorems for (ρ,ψ,d)-Quasiinvex Multiobjective Optimization Problems with Interval-Valued Components

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 894
Author(s):  
Savin Treanţă
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Integral Functional ◽  
Multiple Integral ◽  
Control Problems ◽  
Duality Theorems ◽  
New Class ◽  
Duality Results ◽  
Multiobjective Optimization Problems ◽  
Interval Valued

The present paper deals with a duality study associated with a new class of multiobjective optimization problems that include the interval-valued components of the ratio vector. More precisely, by using the new notion of (ρ,ψ,d)-quasiinvexity associated with an interval-valued multiple-integral functional, we formulate and prove weak, strong, and converse duality results for the considered class of variational control problems.

scholarly journals Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems

2021 ◽  
Author(s):  
Firoz Ahmad
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Practical Implication ◽  
Real Life ◽  
Future Research ◽  
Programming Approach ◽  
Solution Approach ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiobjective Optimization Problems

AbstractThis study presents the modeling of the multiobjective optimization problem in an intuitionistic fuzzy environment. The uncertain parameters are depicted as intuitionistic fuzzy numbers, and the crisp version is obtained using the ranking function method. Also, we have developed a novel interactive neutrosophic programming approach to solve multiobjective optimization problems. The proposed method involves neutral thoughts while making decisions. Furthermore, various sorts of membership functions are also depicted for the marginal evaluation of each objective simultaneously. The different numerical examples are presented to show the performances of the proposed solution approach. A case study of the cloud computing pricing problem is also addressed to reveal the real-life applications. The practical implication of the current study is also discussed efficiently. Finally, conclusions and future research scope are suggested based on the proposed work.

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