15th Anniversary of Axioms: Logic

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Logic".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 271

Editor


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Guest Editor
1. Faculty of Applied Management, Economics and Finance in Belgrade, University Business Academy in Novi Sad, Jevrejska 24, 11000 Belgrade, Serbia
2. College of Global Business, Korea University, Sejong 30019, Republic of Korea
Interests: multiple-criteria decision-making (MCDM); decision support systems (DSSs); computational intelligence; decision-making theory; informatics; management
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Special Issue Information

Dear Colleagues,

Considering that Axioms is celebrating its 15th anniversary, we are pleased to announce a Special Issue in the Logic section that is dedicated to attracting high-quality papers related to recent advances and future directions of mathematical logic, together with multiple-criteria decision-making (MCDM) and computational intelligence (CI).

Mathematical logic, as an important field of mathematics, together with multiple-criteria decision-making (MCDM) and computational intelligence (CI), has a fundamental role in addressing complex decision problems that are characterized by uncertainty, ambiguity, and dynamic environments. This Special Issue will consider high-quality papers in the field of logic, mathematical logic, and their application, with a particular emphasis on computability, fuzzy logic, algorithmic and combinatorial optimization, logic-based intelligent decision-making, innovative MCDM methodologies, hybrid models and integrated approaches, and real-world applications.

We invite scholars to contribute their latest findings and join us in celebrating the continued growth and the impact of the Axioms journal. Therefore, topics include, but are not limited to, the following:

  • Mathematical logic and its applications;
  • Fuzzy systems and fuzzy logic;
  • Computability and recursion theory;
  • Algorithmic and combinatorial optimization;
  • Decision theory and methods;
  • Multiple-criteria decision-making;
  • Decision support systems;
  • Fuzzy, neutrosophic, and grey MCDM methods;
  • Computational intelligence (neural networks, evolutionary algorithms, and swarm intelligence);
  • Probabilistic methods.

Prof. Dr. Darjan Karabašević
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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. Axioms 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 2400 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

  • mathematical logic
  • fuzzy systems and fuzzy logic
  • computability and recursion theory
  • multiple-criteria decision-making
  • computational intelligence

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Published Papers (1 paper)

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Research

30 pages, 983 KB  
Article
Intuitionistic Fuzzy Decision Tree Temporal Logic and Its Application in Engineering Decision-Making
by Xianfeng Yu, Jianhua Zhao, Famin Ma, Lei Wang and Huirong Li
Axioms 2026, 15(6), 456; https://doi.org/10.3390/axioms15060456 (registering DOI) - 18 Jun 2026
Abstract
This paper investigates engineering decision optimization in uncertain environments. Subject to constraints on cost and expected returns, engineering decisions optimize material input, equipment selection and process arrangement to minimize costs and maximize economic benefits. As an efficient formal verification technique, model checking offers [...] Read more.
This paper investigates engineering decision optimization in uncertain environments. Subject to constraints on cost and expected returns, engineering decisions optimize material input, equipment selection and process arrangement to minimize costs and maximize economic benefits. As an efficient formal verification technique, model checking offers a new approach to addressing this problem. Traditional model checking focuses on qualitative verification, while quantitative approaches, including probabilistic and possibilistic model checking, have been gradually developed. Among them, possibilistic model checking is more applicable to systems with fuzzy uncertainty. However, existing possibilistic model-checking techniques have notable limitations: they are only designed for closed systems and ignore interactions between the system and external environments; their simplistic information aggregation leads to information asynchrony and loss; and they cannot model and verify systems with incomplete information. Model checking based on possibilistic decision processes enables the selection of uncertain actions and initially resolves the modeling and verification of open systems. In our previous work, we introduced quality constraints into possibilistic temporal logic to mitigate information asynchrony and loss. We also established the theories of intuitionistic fuzzy Kripke structure (IFKS) and Intuitionistic Fuzzy Computation Tree Logic (IFCTL), which support the modeling and verification of systems with incomplete information. To improve the practicality and accuracy of engineering decisions, this study adopts the ideas of uncertain decision-making behavior selection, quality constraints and incomplete information modeling. It extends IFKS to the Weighted Intuitionistic Fuzzy Kripke Structure (WIFKS) and evolves IFCTL into the intuitionistic fuzzy decision tree logic (IFDTL). We further propose an IFDTL model-checking algorithm and a multi-attribute engineering decision algorithm based on the proposed method, along with corresponding correctness proofs and complexity analysis. A case study on Qinling health-preserving tourism planning verifies the rationality and effectiveness of the presented approach. This research provides a novel formal solution for engineering decision-making under uncertainty. Full article
(This article belongs to the Special Issue 15th Anniversary of Axioms: Logic)
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