A Structural Interaction Framework for Optimization Problems

We consider optimization problems under the structural interaction representa-tionZ(x) = F (x)R(x),where F and R are structural interaction functions. If F and R are differentiable,then∇Z(x) = R(x)∇F (x) + F (x)∇R(x),which characterizes the interaction-induced gradient structure. We establish astructural sufficiency principle: if Z(x) ≥ 0 for all x and Z(x∗) = 0 for some x∗,then x∗ is a global minimizer, and this optimality follows directly from the inter-action structure without convexity assumptions. The framework remains valid fornon-differentiable F and R via generalized derivatives, providing a unified approachto optimization based on structural interaction.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-27
DOI
https://doi.org/10.5281/zenodo.23678951
Primary Topic
Optimization and Variational Analysis
Type
article
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article

A Structural Interaction Framework for Optimization Problems

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

A Structural Interaction Framework for Optimization Problems

DR. ZULFIQAR ALI KHAN
article en

Abstract

We consider optimization problems under the structural interaction representa-tionZ(x) = F (x)R(x),where F and R are structural interaction functions. If F and R are differentiable,then∇Z(x) = R(x)∇F (x) + F (x)∇R(x),which characterizes the interaction-induced gradient structure. We establish astructural sufficiency principle: if Z(x) ≥ 0 for all x and Z(x∗) = 0 for some x∗,then x∗ is a global minimizer, and this optimality follows directly from the inter-action structure without convexity assumptions. The framework remains valid fornon-differentiable F and R via generalized derivatives, providing a unified approachto optimization based on structural interaction.

Zenodo (CERN European Organization for Nuclear Research)
Independent Research Association (RO)
Openalex Percentile: Top 14%
Optimization and Variational Analysis
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