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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Connections between weak-stability and saddle point theorems of the problems are established.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, we focus on weak-stability and saddle point theorems of multiobjective optimization problems that have an infinite number of constraints.
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Key Findings & Data:The obtained results are based on the notion of weak-subdifferentials for vector functions.
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Conclusion & Impact:Connections between weak-stability and saddle point theorems of the problems are established.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Weak-subdifferential · Weak-stability · Strong duality
Abstract
In this paper, we focus on weak-stability and saddle point theorems of multiobjective optimization problems that have an infinite number of constraints. The obtained results are based on the notion of weak-subdifferentials for vector functions. Some properties of weak stability for the problems are introduced. Relationships between strong duality and saddle points of the augmented Lagrange vector functions associated to the problems are investigated. Connections between weak-stability and saddle point theorems of the problems are established. An example is given.
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Cite This Article
SON, T. Q., WEN, C. F. (2019). Weak-stability and saddle point theorems for a multiobjective optimization problem with an infinite number of constraints. Turkish Journal of Mathematics, Cilt: 43 - Sayı: 4, 1953–1966. https://ajindex.com/articles/208983