
Utilitas Mathematica
ISSN: 0315-3681 (print)
Utilitas Mathematica is a historical journal that focuses on sharing research in statistical designs and combinatorial mathematics. It has been publishing since 1972. From 2024 onward, it publishes four volumes per year in March, June, September and December. Utilitas Mathematica has gained recognition and visibility in the academic community and is indexed in renowned databases such as MathSciNet, Zentralblatt, and Scopus. The scope of the journal includes; graph theory, design theory, extremal combinatorics, enumeration, algebraic combinatorics, combinatorial optimization, discrete geometry, convex geometry, Ramsey theory, automorphism groups, coding theory, finite geometries, chemical graph theory, etc.
- Research article
- https://www.doi.org/10.61091/um122-08
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 109-116
- Published Online: 28/03/2025
Some methods of decomposing
- Research article
- https://doi.org/10.61091/um122-07
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 93-108
- Published Online: 23/03/2025
Let
- Research article
- https://doi.org/10.61091/um122-06
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 81-92
- Published Online: 23/03/2025
A special type of algebraic intersection graph called the
- Research article
- https://www.doi.org/10.61091/um122-05
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 65-80
- Published Online: 22/03/2025
Let
- Research article
- https://doi.org/10.61091/um122-04
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 53-64
- Published Online: 22/03/2025
MacMahon extensively studied integer compositions, including the notion of conjugation. More recently, Agarwal introduced
- Research article
- https://doi.org/10.61091/um122-03
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 41-52
- Published Online: 22/03/2025
The covering cover pebbling number,
- Research article
- https://doi.org/10.61091/um122-02
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 29-40
- Published Online: 22/03/2025
Jeff Remmel introduced the concept of a
- Research article
- https://doi.org/10.61091/um122-01
- Full Text
- Utilitas Mathematica
- Volume 122
- Pages: 3-27
Topological Indices (TIs) are quantitative measures derived from molecular geometry and are utilized to predict physicochemical properties. Although more than 3000 TIs have been documented in the published literature, only a limited number of TIs have been effectively employed owing to certain limitations. A significant drawback is the higher degeneracy resulting from the lower discriminative power. TIs utilize simple graphs in which atoms and bonds are conceptualized as the vertices and edges of mathematical graphs. As multiple edges are not supported in these graphs, double and triple bonds are considered single. Consequently, the molecular structure undergoes alterations during the conversion process, which ultimately affects the discriminative power. In this investigation, indices for double-bond incorporation were formulated to preserve structural integrity. This study addresses, demonstrates, and verifies a set of double-bonded indices. The indices demonstrated promising results, exhibiting enhanced discriminative power when validated for polycyclic aromatic hydrocarbons using regression analysis. These indices and their potential applications will significantly contribute to QSAR/QSPR studies.
- Research article
- https://doi.org/10.61091/um121-09
- Full Text
- Utilitas Mathematica
- Volume 121
- Pages: 137-150
- Published: 31/12/2024
With the rapid development of wireless communication networks, it brings more and more convenience to users. However, with the expansion of network size, the limitation of channel resources in network communication is becoming more obvious. Effective channel assignment has a great impact on the quality of communication networks. However, in real communication networks, underutilization of channels and excessive number of channels produce large interference, so it is necessary to find a reasonable channel assignment method. In this paper, we study the optimal channel assignment strategy for the Cartesian product of an
- Research article
- https://doi.org/10.61091/um121-08
- Full Text
- Utilitas Mathematica
- Volume 121
- Pages: 105-135
- Published: 31/12/2024
This study introduces a novel approach to investigating Sombor indices and applying machine learning methods to assess the similarity of non-steroidal anti-inflammatory drugs (NSAIDs). The research aims to predict the structural similarities of nine commonly prescribed NSAIDs using a machine learning technique, specifically a linear regression model. Initially, Sombor indices are calculated for nine different NSAID drugs, providing numerical representations of their molecular structures. These indices are then used as features in a linear regression model trained to predict the similarity values of drug combinations. The model’s prediction performance is evaluated by comparing the predicted similarity values with the actual similarity values. Python programming is employed to verify accuracy and conduct error analysis.
Call for papers
Special issue: Dynamical systems and differential equations in applied sciencesSpecial Issues
The Combinatorial Press Editorial Office routinely extends invitations to scholars for the guest editing of Special Issues, focusing on topics of interest to the scientific community.