DISCRETE APPLIED MATHEMATICS

Scope & Guideline

Empowering Researchers with Cutting-Edge Findings in Discrete Mathematics.

Introduction

Delve into the academic richness of DISCRETE APPLIED MATHEMATICS with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageMulti-Language
ISSN0166-218x
PublisherELSEVIER
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 1979 to 2025
AbbreviationDISCRETE APPL MATH / Discret Appl. Math.
Frequency18 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

Discrete Applied Mathematics focuses on the study and application of discrete structures in mathematics, particularly in relation to combinatorial optimization, graph theory, and algorithm design. The journal serves as a platform for the dissemination of research that bridges theoretical advancements and practical applications in various fields such as computer science, operations research, and applied mathematics.
  1. Graph Theory and Combinatorics:
    The journal emphasizes research on graph structures, properties, and algorithms, exploring topics like graph colorings, matchings, and connectivity.
  2. Algorithm Design and Complexity:
    Research on the development of algorithms for solving combinatorial problems, including complexity analysis and approximation algorithms, is a core focus.
  3. Optimization Problems:
    The journal covers a wide range of optimization problems, including network design, scheduling, and resource allocation, often employing mathematical and algorithmic techniques.
  4. Discrete Structures and Their Applications:
    It includes studies on discrete mathematical structures such as permutations, set systems, and matroids, often with applications in computer science and operations research.
  5. Interdisciplinary Approaches:
    The journal encourages interdisciplinary research that applies discrete mathematics in fields like bioinformatics, social networks, and game theory.
The journal has exhibited a growing interest in several emerging themes, reflecting the current trends in discrete mathematics and its applications. These themes highlight the evolving nature of research and the increasing complexity of the problems being addressed.
  1. Advanced Algorithmic Techniques:
    Research is increasingly focusing on sophisticated algorithmic frameworks, including approximation algorithms, randomized algorithms, and algorithms for NP-hard problems.
  2. Interdisciplinary Applications:
    There is a rising trend in the application of discrete mathematics to interdisciplinary fields such as bioinformatics, network theory, and data science, indicating a broader scope of interest among researchers.
  3. Complex Network Analysis:
    Studies centered around the analysis of complex networks, including social networks and biological networks, are gaining traction, reflecting the importance of understanding interactions in these systems.
  4. Combinatorial Optimization in Real-world Applications:
    Research that applies combinatorial optimization techniques to practical problems, such as logistics, scheduling, and resource allocation, is increasingly prominent.
  5. Graph-based Machine Learning:
    The intersection of graph theory and machine learning is emerging as a significant area of study, with applications in predictive modeling, clustering, and data representation.

Declining or Waning

In recent years, certain themes within Discrete Applied Mathematics have shown a decline in publication frequency, suggesting a waning interest or shifting research focus within the community. These trends may reflect the evolving priorities of researchers or the emergence of new areas of interest.
  1. Classical Graph Theory:
    While foundational topics in graph theory remain important, there is a noticeable decrease in publications focused solely on classical results, such as basic properties of graphs, in favor of more applied and complex problem-solving.
  2. Basic Combinatorial Structures:
    Research on simpler combinatorial structures, such as basic set theory or elementary combinatorial identities, appears to be less frequent, possibly overshadowed by more complex and applied topics.
  3. Elementary Algorithmic Techniques:
    The focus on straightforward algorithmic techniques is diminishing, with more emphasis shifting towards advanced methods, heuristics, and machine learning applications.

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