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Applied Operations Research and Optimization Problems in Network Science

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 1759

Special Issue Editor


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Guest Editor
Electrical Engineering Department, Universidad de Santiago de Chile, Santiago 9170124, Chile
Interests: operations research; combinatorial optimization; telecommunications; graph optimization; convex conic optimization; stochastich and robust optimization
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Special Issue Information

Dear Colleagues,

We invite you to contribute this Special Issue that will explore the intersection of operations research and network sciences, focusing on optimization techniques for analyzing and improving complex networked systems. We invite contributions that address theoretical advancements, algorithmic developments, and real-world applications across various domains, including transportation, telecommunications, supply chains and social networks. The Special Issue’s scope covers a range of optimization challenges, such as graph-based optimization, network flow models, facility location problems, scheduling in networks, the optimization of signal processing and combinatorial optimization. We particularly welcome studies concerning mathematical programming, heuristics, metaheuristics and math-heuristic algorithms. We encourage researchers from academia and industry to submit original research articles, reviews and case studies that contribute to the advancement of this interdisciplinary field.

We look forward to receiving your contributions.

Dr. Pablo Adasme
Guest Editor

Manuscript Submission Information

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Keywords

  • operations research
  • network sciences
  • optimization techniques for analyzing and improving complex networked systems
  • theoretical advancements
  • algorithmic developments
  • real-world applications across various domains
  • transportation
  • telecommunications
  • supply chains
  • social networks
  • graph-based optimization
  • network flow models
  • facility location problems
  • scheduling in networks
  • mathematical programming
  • heuristics
  • meta-heuristics and math-heuristic algorithms
  • signal processing techniques in sensor network telecommunication
  • localization with sensor networks
  • optimization algorithmic approaches

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Published Papers (1 paper)

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Review

28 pages, 3029 KB  
Review
Graph Combinatorial Optimization Problems for Blockchain Transaction Network Analysis
by Michael Palk and Stefan Voß
Mathematics 2026, 14(2), 345; https://doi.org/10.3390/math14020345 - 20 Jan 2026
Viewed by 1347
Abstract
Open data makes it possible to gain insights into the transaction patterns of blockchain projects. These patterns can be modeled as transaction networks, which support a wide range of analytical techniques. Depending on the trade-off between information preservation and complexity reduction, various graph [...] Read more.
Open data makes it possible to gain insights into the transaction patterns of blockchain projects. These patterns can be modeled as transaction networks, which support a wide range of analytical techniques. Depending on the trade-off between information preservation and complexity reduction, various graph representations can be used to capture additional features, temporal changes, and interoperability between protocols. Different analytical approaches, including calculating graph metrics or applying graph neural networks, can reveal hidden structures, uncover unusual activities, detect anomalies, and provide a clearer picture of the dynamics of blockchain projects. While network science metrics and machine learning methods have been extensively applied to transaction networks, graph combinatorial optimization problems remain largely underexplored in this domain, despite their potential to identify critical nodes, hidden substructures, and flow patterns. The goal of this paper is to assess the applicability of graph combinatorial optimization problems to blockchain transaction networks, systematically review existing analytics approaches, discuss their respective strengths and limitations, and explore how combining different techniques can yield deeper insights into the structural and functional properties of blockchain ecosystems. Full article
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