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Algorithms
Special Issues
Graph Algorithms and Graph Labeling
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Graph Algorithms and Graph Labeling

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Combinatorial Optimization, Graph, and Network Algorithms".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 3016

Special Issue Editors

Dr. Ali Ahmad

E-Mail Website
Guest Editor
College of Computer Science and Information Technology, Jazan University, Jazan, Saudi Arabia
Interests: graph algorithms; graph theory; graph labeling; distance in graph; stopological indices
Dr. Muhammad Ahsan Asim

E-Mail Website
Guest Editor
Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City (UMKC), Kansas City, MO, USA
Interests: graph algorithms; graph labeling; topological indices; graph resolvability
Dr. Yilun Shang

E-Mail Website
Guest Editor
Department of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, UK
Interests: mathematics; complex systems; networks; computer science; physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite you to submit your latest research in graph theory and experimental mathematics to this Special Issue, “Graph algorithms and graph labeling”. In applied mathematics, graphs are one of the powerful tools for understanding the objects to determine combinatorial properties. Graph invariants are investigated to map on real time applications in chemical, electrical, electronics, computer and telecommunication engineering. The labeling of temporal graphs (dynamic graphs) is challenging but they have a closer relationship with real-time applications. We are looking for new and innovative approaches of graph labeling, topological indices and metric dimension in coding theory, channel assignment, computer network, layouts of digital circuits, semantic web and social networks. Submissions are welcome to flourish awareness and publication of recent developments in the area of graph properties, methods and applications.

Dr. Ali Ahmad
Dr. Muhammad Ahsan Asim
Dr. Yilun Shang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • complexity issues
  • graph labeling and coloring
  • graph combinatorics
  • distance in graphs
  • graph algorithms
  • approximation algorithms
  • enumerative algorithms
  • number theory and computer security
  • edge metric dimension
  • topological indices
  • mathematical chemistry
  • molecular descriptors
  • extremal graph theory
  • algebraic graph theory
  • resolving sets
  • energy of fraph
  • spectral graph theory

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Published Papers (1 paper)

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Research

23 pages, 1470 KiB  
Article
Progressive Multiple Alignment of Graphs
by Marcos E. González Laffitte and Peter F. Stadler
Algorithms 2024, 17(3), 116; https://doi.org/10.3390/a17030116 - 11 Mar 2024
Cited by 1 | Viewed by 2361
Abstract
The comparison of multiple (labeled) graphs with unrelated vertex sets is an important task in diverse areas of applications. Conceptually, it is often closely related to multiple sequence alignments since one aims to determine a correspondence, or more precisely, a multipartite matching between [...] Read more.
The comparison of multiple (labeled) graphs with unrelated vertex sets is an important task in diverse areas of applications. Conceptually, it is often closely related to multiple sequence alignments since one aims to determine a correspondence, or more precisely, a multipartite matching between the vertex sets. There, the goal is to match vertices that are similar in terms of labels and local neighborhoods. Alignments of sequences and ordered forests, however, have a second aspect that does not seem to be considered for graph comparison, namely the idea that an alignment is a superobject from which the constituent input objects can be recovered faithfully as well-defined projections. Progressive alignment algorithms are based on the idea of computing multiple alignments as a pairwise alignment of the alignments of two disjoint subsets of the input objects. Our formal framework guarantees that alignments have compositional properties that make alignments of alignments well-defined. The various similarity-based graph matching constructions do not share this property and solve substantially different optimization problems. We demonstrate that optimal multiple graph alignments can be approximated well by means of progressive alignment schemes. The solution of the pairwise alignment problem is reduced formally to computing maximal common induced subgraphs. Similar to the ambiguities arising from consecutive indels, pairwise alignments of graph alignments require the consideration of ambiguous edges that may appear between alignment columns with complementary gap patterns. We report a simple reference implementation in Python/NetworkX intended to serve as starting point for further developments. The computational feasibility of our approach is demonstrated on test sets of small graphs that mimimc in particular applications to molecular graphs. Full article
(This article belongs to the Special Issue Graph Algorithms and Graph Labeling)
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