Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 13 min ago
PreprintarXiv licencearXiv

Budget-Constrained Graph Augmentation for Robust Network Design via Kirchhoff Index Minimization

Abstract

Enhancing the robustness of deployed networks against failures and disruptions is critical for reliable operation. This requires deciding which new links to install and how strongly to weight them under limited resources. We study this problem through the Kirchhoff index, or total effective resistance, a spectral measure of global connectivity. The resulting augmentation problem couples discrete candidate-edge selection with continuous weight allocation under heterogeneous per-unit deployment costs, a total budget, and an exact-cardinality constraint. For a fixed weighted base graph, this yields a mixed-integer formulation and a semidefinite relaxation whose optimum lower-bounds the mixed-integer optimum. We cast the relaxation as a cone program and solve it numerically using a homogeneous self-dual embedding and first-order operator splitting. Feasible discrete designs are recovered through rounding-and-repair procedures and assessed by \emph{a posteriori} gap estimates relative to the numerical semidefinite program (SDP) benchmark. As a scalable alternative, we develop an exact-k, budget-feasible greedy heuristic built on rank-one Laplacian updates and biharmonic-distance caching, and interpret its progress through a Bellman value-to-go benchmark with a conservative spectral lower bound on the local policy ratio. Experiments on synthetic and real infrastructure networks across graph sizes, budgets, weight distributions, and cost regimes show that, under fixed budgets, distance-proportional costs limit the achievable resistance reduction and shift installed conductance toward shorter links relative to uniform per-unit costs.

Related

  1. Constrained minimization problem and unbounded dynamics for the four-dimensional Klein-Gordon-Schrödinger System
    Masaru Hamano, Hiroaki Kikuchi, Kenta Tomioka
    arXivPreprintarXiv licenceFull textAnalysis & PDEsarXiv
  2. Nucleation and propagation of brittle fracture as a constrained energy minimization problem
    Oscar Lopez-Pamies, Farhad Kamarei, Gilles A. Francfort +1
    arXivPreprintCC BY-NC-ND 4.0Full textMathematical physicsCondensed matterarXiv
  3. Budget-Constrained Multi-Consensus Decentralized Gradient Descent
    Shuyi Ren, Nicol`o Michelusi, Erik G. Larsson
    arXivPreprintarXiv licenceFull textOptimisation & controlarXiv
  4. Well-posedness and discrete-to-continuum convergence of the Kirchhoff Network model
    Joaquín Oyarzún, Marco Veneroni
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsarXiv
  5. Stability-Constrained Approximation in Spline KANs: Exact Layer Balancing and Budget-Compatible Saturation
    Aleksander Tankman
    arXivPreprintarXiv licenceFull textNumerical analysis & scientific computingStatisticsarXiv
BibTeX
@misc{bhoite2026budgetconstrained,
  title = {{Budget-Constrained Graph Augmentation for Robust Network Design via Kirchhoff Index Minimization}},
  author = {Omkar Bhoite and V Sateeshkrishna Dhuli and Stefan Werner and Kimmo Kansanen},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.29790},
  eprint = {2609.29790},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.29790},
}
RIS
TY  - UNPB
TI  - Budget-Constrained Graph Augmentation for Robust Network Design via Kirchhoff Index Minimization
AU  - Omkar Bhoite
AU  - V Sateeshkrishna Dhuli
AU  - Stefan Werner
AU  - Kimmo Kansanen
PY  - 2026
DA  - 2026/09/24
PB  - arXiv
DO  - 10.48550/arxiv.2609.29790
UR  - https://arxiv.org/abs/2609.29790
AB  - Enhancing the robustness of deployed networks against failures and disruptions is critical for reliable operation. This requires deciding which new links to install and how strongly to weight them under limited resources. We study this problem through the Kirchhoff index, or total effective resistance, a spectral measure of global connectivity. The resulting augmentation problem couples discrete candidate-edge selection with continuous weight allocation under heterogeneous per-unit deployment costs, a total budget, and an exact-cardinality constraint. For a fixed weighted base graph, this yields a mixed-integer formulation and a semidefinite relaxation whose optimum lower-bounds the mixed-integer optimum. We cast the relaxation as a cone program and solve it numerically using a homogeneous self-dual embedding and first-order operator splitting. Feasible discrete designs are recovered through rounding-and-repair procedures and assessed by \emph{a posteriori} gap estimates relative to the numerical semidefinite program (SDP) benchmark. As a scalable alternative, we develop an exact-k, budget-feasible greedy heuristic built on rank-one Laplacian updates and biharmonic-distance caching, and interpret its progress through a Bellman value-to-go benchmark with a conservative spectral lower bound on the local policy ratio. Experiments on synthetic and real infrastructure networks across graph sizes, budgets, weight distributions, and cost regimes show that, under fixed budgets, distance-proportional costs limit the achievable resistance reduction and shift installed conductance toward shorter links relative to uniform per-unit costs.
ER  -