Special Issue "Entropy Method for Decision Making"
Deadline for manuscript submissions: 15 March 2022.
Interests: MCDM and optimization in interval and fuzzy settings; MCDM in an interval valued fuzzy setting; MCDM in the type 2 fuzzy setting; MCDM in an intuitionistic fuzzy setting; MCDM based on the synthesis of fuzzy logic and DST; MCDN based on the synthesis of fuzzy logic; intuitionistic fuzzy sets and DST; development of new methods for modern types of uncertainty processing; applications of MCDM in finance and medical diagnostics
It is well known that any nontrivial decision is burdened with risk. The source of risk is usually a lack of reliable information, in other words, an uncertainty. When making a decision, we usually try to find a compromise between competing criteria of profit (in wide sense) maximization and risk minimization. Thus, some measure of uncertainty is explicitly or implicitly part of decision making. It is important to note that in the most decision making techniques, the criterion of uncertainty minimization is used, but implicitly, without strict mathematical formalization. Although such methods usually provide good results, it seems to be more justified from a methodological point of view to use formalized measures of uncertainty, especially entropy, which plays a key role in the theory of information and has already been successfully used in decision making. Entropy was originally intended to operate with probabilistic uncertainty, but today, in decision making, we deal with a wide spectrum of uncertainties: interval, fuzzy, type 2 fuzzy, interval-valued fuzzy, intuitionistic fuzzy, hesitant fuzzy, evidential (Dempster–Shafer theory of evidence), etc. and their different combinations. In some cases, the basic definition of entropy is adapted to process such types of uncertainty, but generally, there are many new challenges in this field. Therefore, in this Special Issue, we shall encourage the submission of papers devoted to the adaptation of entropy to the solution of multiple criteria decision making (MCDM) problems in the presence of modern types of uncertainty. However, interesting and valuable papers where the problem of uncertainty minimization in MCDM is presented implicitly will be considered as well.
Prof. Dr. Pavel Sevastjanov
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 papers will be 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. Entropy 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 1800 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.
- MCDM and entropy in a probabilistic environment
- MCDM and entropy in a possibilistic setting
- MCDM optimization and entropy in interval and fuzzy settings
- MCDM and entropy in an interval valued fuzzy setting
- MCDM and entropy in a type 2 fuzzy setting
- MCDM in an intuitionistic fuzzy setting
- MCDM and entropy based on the synthesis of fuzzy logic and DST
- MCDN and entropy based on the synthesis of fuzzy logic
- intuitionistic fuzzy sets and DST
- development of new methods for modern types of uncertainty processing
- applications of MCDM and entropy in different fields