ABSTRACT In recent years, we have observed growth in the number of investors in the financial market. This work seeks to improve the decision-making process in real estate investment funds (REITs). To this end, a literature review was carried out in the Scopus database using bibliometrix to analyze the applications of the multicriteria decision aid (MCDA) in the environment of Brazilian REITs. The literature review was used as a basis for structuring the problem and the CATWOE analysis was developed to define the alternatives of the application of a hybrid PSI-CoCoSo method for ordering Brazilian REITs in the corporate sector traded on the São Paulo stock exchange (B3). As a result, the hybrid method proved to be effective in the ranking process, providing robust results on the application and evaluation of Brazilian REITs.

Resumo A Modelagem e Simulação (M&S) permite a reprodução de procedimentos médicos e serviços, a compreensão da progressão de doenças e a previsão de respostas a tratamentos sem riscos a pacientes reais. O objetivo do artigo é simular o sistema de atendimento de ambulâncias do Serviço de Atendimento Móvel de Urgência (SAMU) em uma região do Brasil, utilizando o software Arena e Aprendizado de Máquina (AM). A metodologia quantitativa combina modelagem matemática e estudo de caso para analisar variáveis como número de ambulâncias, chegada de pacientes, tempo de espera e carga de trabalho. Os resultados do Arena alimentaram um modelo de regressão para relacionar tempo de espera e quantidade de ambulâncias, tendo o Protocolo de Manchester como referência. A integração dessas técnicas permitiu prever o impacto de diferentes configurações de recursos. Os resultados numéricos indicaram, com base em dados reais, a redução no tempo de espera com o aumento de ambulâncias, otimizando a distribuição de recursos. Assim, além de contribuir para a eficiência operacional dos serviços móveis de emergência, os resultados fortalecem o desempenho resiliente do Sistema Único de Saúde (SUS) frente a adversidades.

Abstract Modeling and Simulation (M&S) allows for reproducing medical procedures and services, understanding disease progression, and predicting treatment responses without risks to real patients. This study aims to simulate the ambulance service system of the Mobile Emergency Care Service (SAMU) in a Brazilian region, using the Arena software and Machine Learning (ML). The quantitative methodology combines mathematical modeling and a case study to analyze variables such as the number of ambulances, patient arrivals, waiting times, and workload. Using the Manchester Protocol as a reference, the Arena results feed a regression model to relate waiting times and the number of ambulances. Integrating these techniques allowed for predictions regarding the impact of different resource configurations. Based on real data, the numerical results indicated reduced waiting times with increased ambulances and streamlined resource allocation. Thus, by contributing to the operational efficiency of mobile emergency services, the findings also strengthen the resilient performance of the Unified Health System (SUS) in the face of adversities.

Resumen La Modelación y Simulación (M&S) permite la reproducción de procedimientos médicos y servicios, la comprensión de la progresión de enfermedades y la predicción de respuestas a tratamientos sin riesgos para pacientes reales. El objetivo del artículo es simular el sistema de ambulancias del Servicio de Atención Médica de Urgencia (SAMU) en una región de Brasil, utilizando el software Arena y Aprendizaje Automático (AA). La metodología cuantitativa combina modelación matemática y un estudio de caso para analizar variables como el número de ambulancias, llegadas de pacientes, tiempos de espera y carga de trabajo. Los resultados del Arena alimentaron un modelo de regresión para relacionar los tiempos de espera y la cantidad de ambulancias, tomando como referencia el Protocolo de Manchester. La integración de estas técnicas permitió predecir el impacto de diferentes configuraciones de recursos. Los resultados numéricos, basados en datos reales, indicaron una reducción en los tiempos de espera con el aumento de ambulancias, optimizando la distribución de recursos. Así, además de contribuir a la eficiencia operativa de los servicios móviles de emergencia, los resultados fortalecen el desempeño resiliente del Sistema Único de Salud (SUS) frente a las adversidades.

Abstract Modeling and Simulation (M&S) allows for reproducing medical procedures and services, understanding disease progression, and predicting treatment responses without risks to real patients. This study aims to simulate the ambulance service system of the Mobile Emergency Care Service (SAMU) in a Brazilian region, using the Arena software and Machine Learning (ML). The quantitative methodology combines mathematical modeling and a case study to analyze variables such as the number of ambulances, patient arrivals, waiting times, and workload. Using the Manchester Protocol as a reference, the Arena results feed a regression model to relate waiting times and the number of ambulances. Integrating these techniques allowed for predictions regarding the impact of different resource configurations. Based on real data, the numerical results indicated reduced waiting times with increased ambulances and streamlined resource allocation. Thus, by contributing to the operational efficiency of mobile emergency services, the findings also strengthen the resilient performance of the Unified Health System (SUS) in the face of adversities.

Resumo A Modelagem e Simulação (M&S) permite a reprodução de procedimentos médicos e serviços, a compreensão da progressão de doenças e a previsão de respostas a tratamentos sem riscos a pacientes reais. O objetivo do artigo é simular o sistema de atendimento de ambulâncias do Serviço de Atendimento Móvel de Urgência (SAMU) em uma região do Brasil, utilizando o software Arena e Aprendizado de Máquina (AM). A metodologia quantitativa combina modelagem matemática e estudo de caso para analisar variáveis como número de ambulâncias, chegada de pacientes, tempo de espera e carga de trabalho. Os resultados do Arena alimentaram um modelo de regressão para relacionar tempo de espera e quantidade de ambulâncias, tendo o Protocolo de Manchester como referência. A integração dessas técnicas permitiu prever o impacto de diferentes configurações de recursos. Os resultados numéricos indicaram, com base em dados reais, a redução no tempo de espera com o aumento de ambulâncias, otimizando a distribuição de recursos. Assim, além de contribuir para a eficiência operacional dos serviços móveis de emergência, os resultados fortalecem o desempenho resiliente do Sistema Único de Saúde (SUS) frente a adversidades.

Resumen La Modelación y Simulación (M&S) permite la reproducción de procedimientos médicos y servicios, la comprensión de la progresión de enfermedades y la predicción de respuestas a tratamientos sin riesgos para pacientes reales. El objetivo del artículo es simular el sistema de ambulancias del Servicio de Atención Médica de Urgencia (SAMU) en una región de Brasil, utilizando el software Arena y Aprendizaje Automático (AA). La metodología cuantitativa combina modelación matemática y un estudio de caso para analizar variables como el número de ambulancias, llegadas de pacientes, tiempos de espera y carga de trabajo. Los resultados del Arena alimentaron un modelo de regresión para relacionar los tiempos de espera y la cantidad de ambulancias, tomando como referencia el Protocolo de Manchester. La integración de estas técnicas permitió predecir el impacto de diferentes configuraciones de recursos. Los resultados numéricos, basados en datos reales, indicaron una reducción en los tiempos de espera con el aumento de ambulancias, optimizando la distribución de recursos. Así, además de contribuir a la eficiencia operativa de los servicios móviles de emergencia, los resultados fortalecen el desempeño resiliente del Sistema Único de Salud (SUS) frente a las adversidades.

ABSTRACT The study employed the THOR-2 method to select a federal unit (UF) in Brazil’s Midwest and South regions for investments in biodiesel production, considering ESG criteria. Evaluating six criteria, such as actual production and installed capacity, it was identified that Rio Grande do Sul stood out as the best option, for its established capacity, operational efficiency and growth potential. The ranking of UFs highlighted the importance of multi-criteria-based choices, aiming to balance economic impacts with social and environmental benefits. Thus, the study provided a framework for choosing a UF for biodiesel investments and integrated ESG considerations, contributing to sustainability in the energy sector.

ABSTRACT This paper introduces the Group Extended Entropy VIKOR (GE2-VIKOR) MCDM approach for assessing defense technology criticality in developing countries. GE2-VIKOR addresses uncertainty and complexity in this scenario by leveraging VIKOR’s ability to propose compromise solutions in discrete alternatives’ scenarios. GE2-VIKOR can be applied in both individual and group decision-making, incorporating weights based on decision-makers’ knowledge degree and criteria weights determined by the sponsor or Shannon’s entropy theory. The method aims to offer a compromise solution that maximizes group utility while minimizing individual regret under majority, consensus, or veto rules. A detailed demonstration illustrates GE2-VIKOR’s applicability and effectiveness in assessing defense technology criticality in developing countries. The results highlight the method’s strengths and limitations and suggest future research avenues, particularly exploring its applicability in developed countries, where technology criticality concepts differ.

ABSTRACT The purpose of this paper is to prioritize which waste should be treated by Lean Healthcare in a medical clinic of a middle-sized Brazilian hospital, using the multicriteria decision support method THOR 2. It focusses on structuring the problem, establishing alternatives through the study hospital and Lean interventions already made in it, and determining the criteria and parameters of THOR 2 with the help of Value Focus Thinking (VFT) and the hospital directors. THOR 2 was able to identify, taking into account its preference relationships in S2, that establishing a Kanban within the hospital’s medical clinic is the preferred and the main contribution and novelty to the literature is the way that multicriteria methods can help in Lean Healthcare decision making. As conclusions, it was possible to establish a prioritization order, maintaining the concept of continuous improvement, arising from Lean Healthcare, while respecting the limits and restrictions of the hospital.

ABSTRACT The selection process for instructors at the Brazilian Air Force Officers Improvement School (EAOAR) needs improvement to provide clearer guidance to the Commandant. This article aims to streamline and enhance the process by making it more efficient, less subjective, and more reliable. Researchers employed the Analytic Hierarchy Process (AHP) to determine criteria weights and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank candidates. They used Three Decision Methods (3DM) Software Web (v.1) for efficient calculations. Results showed that candidates closer to the Positive Ideal Solution (PIS) received favorable indications, while those closer to the Negative Ideal Solution (NIS) faced rejections. The AHP-TOPSIS hybrid approach successfully ranked candidates and expedited the process. Moreover, this approach has broader applications, including assessing candidates for international missions in the Brazilian Navy and Army, and evaluating employee performance in any organization. Future research could explore classification methods like the ELECTRE-TRI.

ABSTRACT This study analyzes the operational efficiency of Brazil’s 30 largest airports from 2014 to 2018, using a two-stage model. Operational efficiency is defined as an airport’s capacity to effectively utilize resources, such as facilities, staff, and technology, to cater to air traffic and passenger needs. The first stage involved measuring operational efficiency through data envelopment analysis. The second stage used a three-level hierarchical linear model to identify influencing variables. Key findings reveal that location significantly impacts airport efficiency, which generally declined during the study period. The interest rate, the only notable economic factor, had a negative effect on efficiency. Factors like the number of aircraft parking positions, years of airport operation, and the number of airlines positively influenced efficiency. Conversely, governance structure, airport size, commercial establishment count, and vehicle parking lot numbers didn’t notably affect efficiency variation. This methodological approach provided more accurate predictions than traditional regression models.

ABSTRACT The Brazilian Navy (BN) has its combatant force concentrated in an area with only one exit to the sea. Nevertheless, Brazil has an extensive coast that needs to be patrolled and, in case of any kind of conflict, the BN must be able to defend the sovereignty and interests of the country. For this purpose, a robust and decentralized naval force is necessary, which allows the fulfillment of its mission. This paper aims to classify the most suitable cities in Brazil to be established as naval bases by applying the ELECTRE-MOr hybrid method. Seventeen cities were analyzed, which have an opening to the sea and a pre-existing minimum port structure. The alternatives were evaluated by specialists from the BN, with more than twenty years of active service, in the light of operational, economic and strategic criteria. As a result, five alternatives were classified as the most indicated headquarters for the decentralization of the naval power: Belém/PA, São Luis/MA, Fortaleza/CE, Recife/PE and Aratu/BA. This article presents relevance to academia and society, as it represents the application of a method in the state of the art to support the decision-making process in a significant problem for the sovereignty of Brazil, presenting a methodology that can be applied in issues of tactical, operational, strategic and political levels.

Purpose: Multicriteria methods have gained traction in both academia and industry practices for effective decision-making over the years. This bibliometric study aims to explore and provide an overview of research carried out on multicriteria methods, in its various aspects, over the past forty-four years. Design/Methodology/Approach: The Web of Science (WoS) and Scopus databases were searched for publications from January 1945 to April 29, 2021, on multicriteria methods in titles, abstracts, and keywords. The bibliographic data were analyzed using the R bibliometrix package. Findings: This bibliometric study asserts that 29,050 authors have produced 20,861 documents on the theme of multicriteria methods in 131 countries in the last forty-four years. Scientific production in this area grows at a rate of 13.88 per year. China is the leading country in publications with 14.14%; India with 10.76%; and Iran with 8.09%. Islamic Azad University leads others with 504 publications, followed by the Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. As for journals, Expert Systems With Applications; Sustainability; and Journal of Cleaner Production are the leading journals, which account for more than 4.67% of all indexed literature. Furthermore, Zavadskas E. and Wang J have the highest publications in the multicriteria methods domain regarding the authors. Regarding the most commonly used multicriteria decision-making methods, AHP is the most favored approach among the ten countries with the most publications in this research area, followed by TOPSIS, VIKOR, PROMETHEE, and ANP. Practical implications: The bibliometric literature review method allows the researchers to explore the multicriteria research area more extensively than the traditional literature review method. It enables a large dataset of bibliographic records to be systematically analyzed through statistical measures, yielding informative insights. Originality/value: The usefulness of this bibliometric study is summed in presenting an overview of the topic of the multicriteria methods during the previous forty-four years, allowing other academics to use this research as a starting point for their research.

ABSTRACT Military issues have great relevance worldwide since they affect the security and sovereignty of nations. In this context, the application of Multicriteria Decision Analysis (MCDA) methods is important because accurate decision-making is the deciding factor for success, which can reduce expenses and increase defense capacity. This paper aims to present a literature review on the main applications of MCDA in the military area, considering the tactical, operational and strategic spheres. The methodology includes a bibliometric study and literature review of documents from the Scopus and Web of Science databases. The bibliometric study identified the document type, language, year of publication, authors, author network, author’s publications, affiliation, keyword clusters, the field of knowledge, country and the main applied MCDA methods in military problems. The literature review allows us to verify that, as well as in other areas of knowledge, the Analytic Hierarchy Process (AHP) is the most applied MCDA method in the military area.

Abstract Paper aims This paper aims to select the best helicopter to be acquired by the Brazilian Navy (BN), enabling greater logistical and combat capacity in marine operations. For this purpose, we applied the AHP-TOPSIS-2N, a hybrid multicriteria method composed by the Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and two normalization procedures (2N). Originality In this paper, a real military case study is conducted to support the decision-making process in BN, contributing to the better performance of the Brazilian Armed Forces. The application of the methodology resulted in two lists of ordering and prioritization of helicopters, providing transparency and simplicity to the decision-making process. Research method We analyzed six aircraft models, considering attack helicopters used by the Armed Forces of developed countries, in the light of their operational and tactical criteria. The selected helicopter would be employed in the fire support and reconnaissance, required by the Brazilian Marine Corps Amphibious Operations. Main findings After the application of the method, the AH-64E APACHE was chosen as the most suitable helicopter to be acquired by the Brazilian Navy. Implications for theory and practice This study brings valuable contribution to academia and society, since it represents the application of a Multi-criteria Decision Analysis (MCDA) method in the state of the art to contribute to the solution of a real problem of the BN. The methodology presented in this paper can notably be used to solve real problems of the most varied types – tactical, operational and strategic – thus being a very useful method for decision-making.

ABSTRACT This paper proposes a new ordinal method to rank alternatives with multiple criteria and decision makers (DMs). This is a decision group ordinal method called SAPEVO-M, an acronym for Simple Aggregation of Preferences Expressed by Ordinal Vectors Group Decision Making. SAPEVO-M method allows for the aggregation of DM preference rankings into a consensus ranking and expresses the DM degrees of importance in the form of a rank order. It was developed for dealing with purely ordinal criteria and it is also applicable to situations in which ordinal and cardinal criteria are intermixed. A free version of the method was made available on the internet.

RESUMO OBJETIVO: Aplicar o método multicritério THOR 2 para selecionar o navio de assistência hospitalar (NAsH) da Marinha do Brasil mais indicado para apoiar o combate à pandemia de covid-19. MÉTODOS: Para a estruturação e modelagem do problema, foram usados os três primeiros estágios da Soft Systems Methodology. Já para a avaliação e ordenação das alternativas, foi utilizado o método de análise multicritério Thor 2, comparando quatro classes de NAsH à luz de seus critérios operativos e hospitalares: “Dr. Montenegro”, “Soares Meirelles”, “Oswaldo Cruz” e “Tenente Maximiano”. O navio escolhido apoiaria o sistema hospitalar do Amazonas, que apresenta número cada vez maior de casos de covid-19. RESULTADOS: Após a aplicação dos métodos, foi possível analisar três cenários distintos de ordenação das alternativas, o que permitiu uma análise de sensibilidade robusta, conferindo maior transparência e confiabilidade ao processo decisório. O NAsH “Oswaldo Cruz” foi selecionado para ser empregado no combate à pandemia. CONCLUSÕES: Este trabalho traz valiosa contribuição para academia e sociedade, uma vez que representa a aplicação de um método de auxílio à decisão multicritério no estado da arte para contribuir com a solução de um problema real que afeta milhões de pessoas no Brasil e no mundo.

ABSTRACT OBJECTIVE: To apply the THOR 2 multi-criteria support system to select the Brazilian navy's most suitable hospital care vessel (NAsH) to support the fight against the covid-19 pandemic. METHODS: We used the first three stages of the Soft Systems Methodology for structuring and modeling of the problem. For the evaluation and ordering of alternatives, we used the Thor 2 multi-criteria support system, comparing four classes of NAsH in the light of their operational and hospital criteria: “Dr. Montenegro,” “Soares Meirelles,” “Oswaldo Cruz” and “Tenente Maximiano.” The chosen ship would support the amazon hospital system, which has an increasing number of cases of covid-19. RESULTS: After the application of the methods, we analyzed three distinct scenarios of ordering the alternatives, which allowed a robust sensitivity analysis, conferring greater transparency and reliability to the decision-making process. The NAsH “Oswaldo Cruz” was selected to be used in the fight against the pandemic. CONCLUSIONS: This study brings valuable contribution to academia and society, since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.

RESUMO OBJETIVO: Aplicar o método multicritério THOR 2 para selecionar o navio de assistência hospitalar (NAsH) da Marinha do Brasil mais indicado para apoiar o combate à pandemia de covid-19. MÉTODOS: Para a estruturação e modelagem do problema, foram usados os três primeiros estágios da Soft Systems Methodology. Já para a avaliação e ordenação das alternativas, foi utilizado o método de análise multicritério Thor 2, comparando quatro classes de NAsH à luz de seus critérios operativos e hospitalares: “Dr. Montenegro”, “Soares Meirelles”, “Oswaldo Cruz” e “Tenente Maximiano”. O navio escolhido apoiaria o sistema hospitalar do Amazonas, que apresenta número cada vez maior de casos de covid-19. RESULTADOS: Após a aplicação dos métodos, foi possível analisar três cenários distintos de ordenação das alternativas, o que permitiu uma análise de sensibilidade robusta, conferindo maior transparência e confiabilidade ao processo decisório. O NAsH “Oswaldo Cruz” foi selecionado para ser empregado no combate à pandemia. CONCLUSÕES: Este trabalho traz valiosa contribuição para academia e sociedade, uma vez que representa a aplicação de um método de auxílio à decisão multicritério no estado da arte para contribuir com a solução de um problema real que afeta milhões de pessoas no Brasil e no mundo.

ABSTRACT OBJECTIVE: To apply the THOR 2 multi-criteria support system to select the Brazilian navy's most suitable hospital care vessel (NAsH) to support the fight against the covid-19 pandemic. METHODS: We used the first three stages of the Soft Systems Methodology for structuring and modeling of the problem. For the evaluation and ordering of alternatives, we used the Thor 2 multi-criteria support system, comparing four classes of NAsH in the light of their operational and hospital criteria: “Dr. Montenegro,” “Soares Meirelles,” “Oswaldo Cruz” and “Tenente Maximiano.” The chosen ship would support the amazon hospital system, which has an increasing number of cases of covid-19. RESULTS: After the application of the methods, we analyzed three distinct scenarios of ordering the alternatives, which allowed a robust sensitivity analysis, conferring greater transparency and reliability to the decision-making process. The NAsH “Oswaldo Cruz” was selected to be used in the fight against the pandemic. CONCLUSIONS: This study brings valuable contribution to academia and society, since it represents the application of a multi-criteria decision-aid method in the state of the art to contribute to the solution of a real problem that affects millions of people in Brazil and worldwide.