Title | ||
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The optimality conditions for optimization problems with convex constraints and multiple fuzzy-valued objective functions |
Abstract | ||
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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 |
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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 |
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Hsien-Chung Wu | 1 | 565 | 53.02 |