Paper Info
Title
The optimality conditions for optimization problems with convex constraints and multiple fuzzy-valued objective functions
Abstract
The optimality conditions for multiobjective programming problems with fuzzy-valued objective functions are derived in this paper. The solution concepts for these kinds of problems will follow the concept of nondominated solution adopted in the multiobjective programming problems. In order to consider the differentiation of fuzzy-valued functions, we invoke the Hausdorff metric to define the distance between two fuzzy numbers and the Hukuhara difference to define the difference of two fuzzy numbers. Under these settings, the optimality conditions for obtaining the (strongly, weakly) Pareto optimal solutions are elicited naturally by introducing the Lagrange multipliers.
Year
DOI
Venue
2009
10.1007/s10700-009-9061-6
FO & DM
Keywords
Field
DocType
Hausdorff metric,Hukuhara difference,H-differentiability,Lagrange multipliers,Pareto optimal solution
Discrete mathematics,Mathematical optimization,Lagrange multiplier,Fuzzy logic,Multiobjective programming,Regular polygon,Hausdorff distance,Fuzzy number,Karush–Kuhn–Tucker conditions,Optimization problem,Mathematics
Journal
Volume
Issue
ISSN
8
3
1568-4539
Citations 
PageRank 
References 
9
0.69
9
Authors
1
Name
Order
Citations
PageRank
Hsien-Chung Wu156553.02