On Pair Invexity and Compromise Duality in Mathematical Programming

Classical invexity ensures sufficiency of the Karush–Kuhn–Tucker (KKT) conditionsfor nonlinear programming, but it relies on a single mapping η(x, u) and fails when feasibledirections depend on interacting components. In this paper we introduce Pair Invexity, ageneralization defined via a coupled mapping P : X × X → Rn. A differentiable functionf : X → R is Pair Invex at u ∈ X with respect to P iff (x) − f (u) ≥ ∇f (u)T P (x, u), ∀x ∈ X, (1)where P (x, u) = Ψ(η1(x, u), η2(x, u)) combines two directional mappings η1, η2 throughΨ. Under Pair Invexity, we prove that the KKT conditions are sufficient for global opti-mality and establish a single duality theorem that provides both a valid lower bound andzero duality gap at optimality. The framework unifies and extends invexity, Φ-invexity, andadditive invexity, and is illustrated with nonconvex examples where classical invexity fails.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-17
DOI
https://doi.org/10.5281/zenodo.22812936
Primary Topic
Optimization and Variational Analysis
Type
article
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On Pair Invexity and Compromise Duality in Mathematical Programming

DR. ZULFIQAR ALI KHAN
Zenodo (CERN European Organization for Nuclear Research)
Optimization and Variational Analysis
article

On Pair Invexity and Compromise Duality in Mathematical Programming

DR. ZULFIQAR ALI KHAN
article en

Abstract

Classical invexity ensures sufficiency of the Karush–Kuhn–Tucker (KKT) conditionsfor nonlinear programming, but it relies on a single mapping η(x, u) and fails when feasibledirections depend on interacting components. In this paper we introduce Pair Invexity, ageneralization defined via a coupled mapping P : X × X → Rn. A differentiable functionf : X → R is Pair Invex at u ∈ X with respect to P iff (x) − f (u) ≥ ∇f (u)T P (x, u), ∀x ∈ X, (1)where P (x, u) = Ψ(η1(x, u), η2(x, u)) combines two directional mappings η1, η2 throughΨ. Under Pair Invexity, we prove that the KKT conditions are sufficient for global opti-mality and establish a single duality theorem that provides both a valid lower bound andzero duality gap at optimality. The framework unifies and extends invexity, Φ-invexity, andadditive invexity, and is illustrated with nonconvex examples where classical invexity fails.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 9%
Optimization and Variational Analysis
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