LINEAR SEARCH ALGORITHM FOR STRONGLY CONNECTED COMPONENTS IN DIRECTED GRAPHS BASED ON THE ANALYSIS OF THE MATRIXS TRANSITIVE CLOSURE OF BINARY RELATIONS
DOI:
https://doi.org/10.15588/1607-3274-2026-2-13Keywords:
network object, object damage, directed graph, graph vertex, transitive closure, strongly connected component, matrix, main diagonal of the matrix, unit block, algorithmAbstract
Context. The relevance of the article is due to the need for further development of simple algorithms for analyzing the structural connectivity of network objects, in reducing the computational complexity and increasing the functional capabilities of such algorithms. The linear algorithm proposed in the article can be applied: in urban and rural transport route planning systems; in solving various types of problems related to carrying out restoration work on network objects after their destruction and the loss of certain connections between the elements of such objects (power supply systems, communication systems, transport networks, etc.); in developing options for effectively destroying key objects of the enemy’s critical infrastructure; in analyzing social networks for grouping individuals into groups by interest, etc.
Objective. The goal of the work is to develop a linear algorithm for searching for strongly connected components in the structure of network objects, which is resistant to changes in the structure of objects and has a polynomial computational complexity.
Method. The physical object to be studied is modeled by a connected directed graph. To determine the structure of the model graph components of strong connectivity, the idea of analyzing the presence of direct and reverse transitive closures between all pairs of vertices of the model graph was applied. Since there is a route (or arc) connecting them between all pairs of vertices included in any component of strong connectivity, then in the matrix of transitive closures of binary relations of such a graph there will always be unit blocks (transitivity compactions). Individual elements of these blocks in the matrix of transitive closures are scattered in a certain way. By analyzing the matrix for the presence of identical rows and identical columns, it is possible to establish their belonging to certain unit blocks. After such analysis and grouping the corresponding rows and columns into unit blocks, it is possible to determine the number of components of strong connectivity, as well as the index (vertex) composition of each component.
To construct a matrix of transitive closures of binary relations, any of the known algorithms can be used, as discussed in the article. Therefore, the linear algorithm proposed in this article is conventionally divided into two main stages: the first is the search for transitive closures of binary relations of a model directed graph; the second is the determination of the matrix of inverse reachability of the graph, the determination of the matrix of mutual reachability, and the search for unit blocks in the latter by lining them up on the main diagonal of the matrix.
Results. 1) A theoretical basis for analyzing the matrix of transitive closures of binary relations of a model directed graph has been developed in order to determine the quantitative and index composition of strongly connected components in its composition; 2) In terms of graph theory, the search for strongly connected components in the structure of a network object is formalized; 3) The developed algorithm was verified for its ability to determine strongly connected components in the structure of a directed graph.
Conclusions. Theoretical studies and a number of experiments confirm the possibility of using the proposed algorithm in the tasks of structural analysis of network objects. Since the well-known provisions of graph theory were used in the theoretical studies, which are interpreted unambiguously in this theory, the absence of any probabilistic processes allows us to consider the developed algorithm accurate. Polynomial estimates of its computational complexity allow it to be used in real-time scale
References
Cormen T. H. et al. Introduction to algorithms. Cambridge, MIT Press, 2009, 1292 p.
Aho A. V., Hopcroft J. E. , Ullman Jeffrey D. The Design and Analysis of Computer Algorithms. [S. l.]. Addison-Wesley, 1974, 482 p.
Demetrescu C., Italiano G. F. Fully Dynamic Transitive Closure: Breaking Through the O(n²) Barrier. Proceedings of FOCS 2000, [S. l.], 2000, pp. 381–389.
Tarjan R. E. Depth-first search and linear graph algorithms. SIAM Journal on Computing, 1972, Vol. 1, No. 2, pp. 146–160.
Gabow H. N. Path-based depth-first search for strong and biconnected components. Information Processing Letters, 2000, Vol. 74, № 3–4, pp. 107–114.
Christofides N. Theory of graphs : algorithmic approach. Moscow, Mir, 1978, 432 p.
Alshomrani S., Iqbal G. An extended experimental evaluation of SCC (Gabow’s vs Kosaraju’s) based on adjacency list. Global Journal of Computer Science and Technology. Series E, Network, Web & Security, 2013, Vol. 13, № 11, pp. 68–74. ISSN 0975-4350
Tarjan R. E., Zwick U. Finding strong components using depth-first search. European Journal of Combinatorics, 2024, Vol. 119, № 2, Art. 103815. DOI: 10.1016/j.ejc.2023.103815
Dhingra S., Dodwad P. S., Madan M. Finding strongly connected components in a social network graph. International Journal of Computer Applications, 2016, Vol. 136, № 7, pp. 1–5. DOI: 10.5120/ijca2016908481
Nuutila E., Soisalon-Soininen E. O. On finding the strongly connected components in a directed graph. Information Processing Letters, 1994, Vol. 49, № 1, pp. 9–14. DOI: 10.1016/0020-0190(94)90047-7.
Lipskyy V. Combinatory for programmers. Moscow, Mir Press, 1988, 213 p.
Warshall S. Algorithm on Boolean matrices. Journal of the ACM, 1962, Vol. 9, № 1, pp. 11–12. DOI: 10.1145/321105.321107
Floyd R. Algorithm 97: Shortest path. Communications of the ACM, 1961, Vol. 5, № 6, P. 345. DOI: 10.1145/367766.368168
Warren H. A modification of Warshall’s algorithm for the transitive closure of binary relations, Communications of the ACM, 1975, Vol. 18, № 4, pp. 218–220.
Bellman R. On a Routing Problem. Quarterly of Applied Mathematics, 1958, Vol. 16, № 1, pp. 87–90.
Shimbel A. Structural parameters of communication networks. Bulletin of Mathematical Biophysics, 1953, Vol. 15, № 4, pp. 501–507. DOI: 10.1007/BF02476438
Batsamut V., Manzura S., Kosiak O. et al. Fast Algorithm for Calculating Transitive Closures of Binary Relations in the Structure of a Network Object. International Journal of Computing, 2021, Vol. 20, № 4, pp. 560–566. DOI: 10.47839/ijc.20.4.2444
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 V. M. Batsamut, Y. H. Bashkatov, D. A. Morkvin, D. Yu. Tolstonosov, B. V. Sakhnevych, Y. M. Solodun

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Creative Commons Licensing Notifications in the Copyright Notices
The journal allows the authors to hold the copyright without restrictions and to retain publishing rights without restrictions.
The journal allows readers to read, download, copy, distribute, print, search, or link to the full texts of its articles.
The journal allows to reuse and remixing of its content, in accordance with a Creative Commons license СС BY -SA.
Authors who publish with this journal agree to the following terms:
-
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License CC BY-SA that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
-
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
-
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.