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Algorithms
Special Issues
Algorithms and Models for Dynamic Multiple Criteria Decision Making II
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Algorithms and Models for Dynamic Multiple Criteria Decision Making II

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 8670

Special Issue Editors

Dr. Debora Di Caprio

E-Mail Website
Guest Editor
Department of Economics and Management, University of Trento, Trento, Italy
Interests: optimization; operations management; mathematical modelling; linear programming; social influence; mathematical programming; economic theory; heuristics
Special Issues, Collections and Topics in MDPI journals
Dr. Francisco Javier Santos-Arteaga

E-Mail Website
Guest Editor
Faculty of Economics and Management, Free University of Bolzano, Piazza Università, 1, 39100 Bolzano BZ, Italy
Interests: decision theory; operations research; information sciences; innovation; economic growth; institutional economics; wine economics; multiple criteria decision making; organ transplantation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The substantial increment in the applications of multiple criteria decision making (MCDM) techniques observed in recent years illustrates both their malleability and acceptance as problem-solving methods when dealing with conflicting criteria. Despite the impressive evolution of this research area, there is still ample room for additional improvements dealing with unexplored—though essential—research aspects. The induction of standard MCDM methods within the domain of dynamical systems is one of the most immediate improvements to be made.

When dealing with conflicting objectives, the design of specific algorithms and heuristic methods seems restricted to their implementation within multi-objective optimization problems, particularly when analyzing complex structures involving dynamic or strategic interactions across variables. The current Special Issue aims at integrating MCDM methods, such as TOPSIS, VIKOR, PROMETHEE and ELECTRE, within the domain of dynamical systems. In particular, it aims at bridging the gap existing between standard MCDM methods—generally implemented within static environments—and the dynamic interactions taking place across variables in many real-life settings.

An intuitive example regarding the preferred type of research is provided by the different dynamic extensions of data envelopment analysis (DEA) introduced in the operational research literature. In addition to the inclusion of a temporal dimension across MCDM methods, any potential development in techniques such as dynamic DEA or novel extensions of multi-objective optimization problems involving dynamic interactions across variables are welcome as contributions to the current Special Issue.

Dr. Debora Di Caprio
Dr. Francisco Javier Santos-Arteaga
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

  • Multiple criteria decision making
  • Dynamical systems
  • Algorithms
  • Data envelopment analysis
  • TOPSIS
  • VIKOR
  • PROMETHEE
  • ELECTRE
  • Multiobjective optimization
  • Uncertainty
  • Artificial Intelligence
  • Machine learning.

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Published Papers (3 papers)

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12 pages, 1116 KiB  
Article
A Simplified Algorithm for Dealing with Inconsistencies Using the Analytic Hierarchy Process
by Sean Pascoe
Algorithms 2022, 15(12), 442; https://doi.org/10.3390/a15120442 - 23 Nov 2022
Cited by 7 | Viewed by 2230
Abstract
Inconsistencies in the comparison matrix is a common problem in many studies using the analytic hierarchy process (AHP). While these may be identified and corrected through asking respondents to reconsider their choices, this is not always possible. This is particularly the case for [...] Read more.
Inconsistencies in the comparison matrix is a common problem in many studies using the analytic hierarchy process (AHP). While these may be identified and corrected through asking respondents to reconsider their choices, this is not always possible. This is particularly the case for online surveys, where the number of respondents may be large and often anonymous, such that interacting with individual respondents is neither feasible nor possible. Several approaches have previously been developed for autonomously adjusting the comparison matrix to deal with inconsistencies. In this paper, we build on these previous approaches, and present an algorithm that is conceptually and analytically simple and readily implementable in R. The algorithm is applied to several example cases to illustrate its performance, including an example case study involving data collected through a large online survey. The results suggest that the modified survey-derived comparison matrix derived using the algorithm produces consistent responses that do not substantially alter the individual preferences in most cases. Full article
(This article belongs to the Special Issue Algorithms and Models for Dynamic Multiple Criteria Decision Making II)
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31 pages, 2897 KiB  
Article
A Systematic Approach to the Management of Military Human Resources through the ELECTRE-MOr Multicriteria Method
by Igor Pinheiro de Araújo Costa, Adilson Vilarinho Terra, Miguel Ângelo Lellis Moreira, Maria Teresa Pereira, Luiz Paulo Lopes Fávero, Marcos dos Santos and Carlos Francisco Simões Gomes
Algorithms 2022, 15(11), 422; https://doi.org/10.3390/a15110422 - 9 Nov 2022
Cited by 15 | Viewed by 2463
Abstract
Personnel selection is increasingly proving to be an essential factor for the success of organizations. These issues almost universally involve multiple conflicting objectives, uncertainties, costs, and benefits in decision-making. In this context, personnel assessment problems, which include several candidates as alternatives, along with [...] Read more.
Personnel selection is increasingly proving to be an essential factor for the success of organizations. These issues almost universally involve multiple conflicting objectives, uncertainties, costs, and benefits in decision-making. In this context, personnel assessment problems, which include several candidates as alternatives, along with several complex evaluation criteria, can be solved by applying Multicriteria Decision Making (MCDM) methods. Uncertainty and subjectivity characterize the choice of personnel for missions or promotions at the military level. In this paper, we evaluated 30 Brazilian Navy officers in the light of four criteria and 34 subcriteria. To support the decision-making process regarding the promotion of officers, we applied the ELECTRE-Mor MCDM method. We categorized the alternatives into three classes in the modeling proposed in this work, namely: Class A (Promotion by deserving), Class B (Promotion by seniority), and Class C (Military not promoted). As a result, the method presented 20% of the officers evaluated with performance corresponding to class A, 53% of the alternatives to class B, and 26.7% with performances attributed to class C. In addition, we presented a sensitivity analysis procedure through variation of the cut-off level λ, allowing decision-making on more flexible or rigorous scenarios at the discretion of the Naval High Administration. This work brings a valuable contribution to academia and society since it represents the application of an MCDM method in state of the art to contribute to solving a real problem. Full article
(This article belongs to the Special Issue Algorithms and Models for Dynamic Multiple Criteria Decision Making II)
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20 pages, 4176 KiB  
Article
A Novel MCDA-Based Methodology Dealing with Dynamics and Ambiguities Resulting from Citizen Participation in the Context of the Energy Transition
by Sadeeb Simon Ottenburger, Stella Möhrle, Tim Oliver Müller and Wolfgang Raskob
Algorithms 2022, 15(2), 47; https://doi.org/10.3390/a15020047 - 28 Jan 2022
Cited by 1 | Viewed by 2714
Abstract
In the context of the energy transition, sound decision making regarding the development of renewable energy systems faces various technical and societal challenges. In addition to climate-related uncertainties affecting technical issues of reliable grid planning, there are also subtle aspects and uncertainties related [...] Read more.
In the context of the energy transition, sound decision making regarding the development of renewable energy systems faces various technical and societal challenges. In addition to climate-related uncertainties affecting technical issues of reliable grid planning, there are also subtle aspects and uncertainties related to the integration of energy technologies into built environments. Citizens’ opinions on grid development may be ambiguous or divergent in terms of broad acceptance of the energy transition in general, and they may have negative attitudes towards concrete planning in their local environment. First, this article identifies the issue of discrepancies between preferences of a fixed stakeholder group with respect to the question of the integration of renewable energy technology, posed from different perspectives and at different points in time, and considers it as a fundamental problem in the context of robust decision making in sustainable energy system planning. Second, for dealing with that issue, a novel dynamic decision support methodology is presented that includes multiple surveys, statistical analysis of the discrepancies that may arise, and multicriteria decision analysis that specifically incorporates the opinions of citizens. Citizens are considered as stakeholders and participants in smart decision-making processes. A case study applying agent-based simulations underlines the relevance of the methodology proposed for decision making in the context of renewable energies. Full article
(This article belongs to the Special Issue Algorithms and Models for Dynamic Multiple Criteria Decision Making II)
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