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October 27, 2025Journal of Combinatorial Mathematics and Combinatorial Computing0 citationsOpen Access

Sharp bounds of partition resolvability of convex polytopes

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KAKamran Azhar

Key Points

  • Partition dimension of convex polytopes shows NP-hard complexity, highlighting the challenge in determining accurate values.
  • Analysis of convex polytopes includes fundamental concepts like faces and duality, essential for understanding geometric structures.
  • Employing graph theory provides a critical framework for analyzing network structures and their mathematical underpinnings.
  • Findings may enable advancements in resolving complex network design issues through refined geometric insights.

Abstract

Graph theory serves as a central and dynamic framework for the design and analysis of networks. Convex polytopes, as fundamental geometric entities, encompass a rich variety of mathematical structures and problems. The basic theory of convex polytopes involves the study of faces, normal cones, duality—particularly polarity—along with separation and other elementary concepts. A convex polytope can be described as a convex set of points within the \ (n\) -dimensional Euclidean space \ (^n\). Among the various dimensions, the partition dimension is the most challenging, and determining its exact value is an NP-hard problem. In this work, we establish bounds for the partition dimension of convex polytopes \ (T_\), \ (R_\), and \ (U_\).

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Cite This Study

Kamran Azhar (2025) studied this question.

synapsesocial.com/papers/68ff87e2c8c50a61f2bdcf52https://doi.org/10.61091/jcmcc128-10
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Also Consider

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  1. 1On Sharp Bounds of Fault-Tolerant Partition Dimension of Convex Polytopes2025
  2. 2Fractional Strong Metric Dimension of Convex Polytopes and its applications2024
  3. 3Fault-tolerant resolvability of some graphs of convex polytopes2023
  4. 4Discrete Curvatures and Convex Polytopes2025
  5. 5The Nonlocal Metric Dimension of Some Convex Polytopes2025