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ABSTRACT In this study, optimization models for the production and logistics tactical planning of the corn supply chain are presented and several outputs are explored. They consider the domestic market for animal consumption, ethanol production, and the international market. They are mainly oriented to support policies and decisions of public agents who have some interference in the supply chain. To evaluate the consistency and effectiveness of the models, they were applied to solve realistic problem instances of the Brazilian corn supply chain considering different scenarios and using data collected from several sources. The outcomes demonstrated that models can produce analysis considering aspects that have not been fully addressed in the literature before, such as some opportunities to use different modes of transport for corn distribution, to contract extra capacity for stocking and the impacts of some state taxes on its production and logistic systems. Other important aspects explored in the scenario analysis are the identification of capacity bottlenecks and investment opportunities. The conclusions and insights are converted into practical interpretations to support relevant supply chain decisions.

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ABSTRACT With the growth of the demand flow and its variability at an emergency department, the complexity to deal with the prioritization of assistance also increases, seeking to offer a quality service. In this sense, several systematized risk triage protocols were created to organize the queues at the emergency, establishing an order of service to ensure that patients do not wait more than a safe time to receive their first medical care. Therefore, the objective of this work is to analyze and evaluate the behavior of an emergency department using a discrete event simulation model. For the results, it was possible to better understand the patient flow, identify problems and difficulties in the system, propose alternatives to deal with patient prioritization, and evaluate the performance of these alternatives through the Goal Question Metric methodology.

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ABSTRACT This work presents an integrated decision support process based on Value-Focused Thinking (VFT) applicable to personal and organizational decisions. There are three main goals of this research: (i) present a methodological discussion on Value-Focused Thinking (VFT) and depict how it can contribute to support decision processes; (ii) present an integrated guide for a decision-support process based on VFT to help analysts and decision-makers in conducting decision processes; (iii) present applications of the proposed approach in a personal and a public management problem. This work delivers two main contributions: (a) a unified process that integrates different approaches based on VFT with a consistent structure for sequencing the stages of the decision-making process; and (b) examples that demonstrate the use of the proposed process in real problems and different contexts, presenting insights not thoroughly explored in the literature.

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ABSTRACT We study a class of integer bilevel problems, the so-called Integer Linear Multiplicative Bilevel Problem, ILMBP, where the constraints are linear and both the upper level problem and the lower level problem are integer linear multiplicative problems. We assume that the k -linear factors of the upper level problem and the l -linear factors of the lower level problem to be non-negative. In this paper, we propose an algorithm based on branch-and-cut method for solving the Integer Linear Multiplicative Bilevel Problem. First, the continuous upper level linear multiplicative problem is solved, then the optimal integer solution obtained is tested for the optimality of the main problem by solving the lower level linear multiplicative problem. If this solution is not optimal for the problem ILMBP, a cut is added to the upper level problem and a new best integer solution is determined. The integer solution is generated by the branching process well known in the branch and bound procedure. Following, the presentation and validation of the algorithm, an example is provided to better visualize the algorithm.

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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.

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ABSTRACT This research evaluates the quality of life of the ninety-two cities in the state of Rio de Janeiro using a non-compensatory composite aggregator index. It was a multimethodological research, which combines a qualitative conceptual map with a quantitative multicriteria model to assess variables of difficult definition. The criteria are based on Maslow’s concepts, which also define the weights between them, bringing more coherence to the index. We conclude that our measurement model with non-compensatory rationality offers an alternative for calculating the quality of life. The cities of Niteroi, Rio de Janeiro and Volta Redonda scored best in our proposed index. Silva Jardim, Sumidouro and São Francisco de Itabapoana scored worst. Niteroi scored best in Physiological and Esteem needs. Nova Friburgo scored best in Safety needs. Mesquita scored best in Love and belonging needs. A sensitivity analysis shows that our method’s structure makes results distortion difficult.

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ABSTRACT Waste sorting is a core element for adding value to the recycling chain. Exploring and prioritizing alternatives regarding its expansion and improvement is very challenging. This study proposes a multi-methodological approach through the integration of a Problem Structuring Method (PSM) and a multicriteria method (MCDA/M) to support decision-making in the solid waste management context. The developed model uses Soft Systems Methodology (SSM) in the problem structuring stage to explore the problematic situation and identify alternatives. Preference modeling was conducted in a flexible and interactive manner, aided by FITradeoff method to rank the identified alternatives and obtain a recommendation. The proposed model was developed for a real case study in Brazil. In the elicitation process, the decision maker answered 9 questions to obtain the ordering of alternatives. This work seeks to enrich the literature proposing the successful application of an innovative model in the waste management context, especially regarding waste sorting.

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ABSTRACT Facility location-related decision problems pose a significant challenge for managers due to the multiple and conflicting factors involved. Moreover, incorrect decisions can lead to substantial impacts on companies' long-term strategic planning, resulting in losses for the business. This paper deals with a facility location problem in the educational sector in the northeast region of Brazil, which concerns the definition of the best location to place a private sector technical school, considering multiple objectives throughout a multicriteria approach. The decision-making process is structured based on a 9-step multicriteria model, and the preference elicitation phase is aided by the Flexible and Interactive Tradeoff (FITradeoff) method, using partial information provided by the decision-maker (DM). In the application presented in this paper, preference modeling is conducted considering the combination of two preference elicitation paradigms in the FITradeoff decision process: elicitation by decomposition and holistic evaluations, throughout a flexible approach. The DM’s preferences are elicited interactively, by means of a Decision Support System (DSS). At each interaction, the information given by the DM acts as constraints for a linear programming problem (LPP) model, which is computed in order to verify the potential optimality of each alternative. At the end of the elicitation process, a sensitivity analysis is performed so as to verify the robustness of the results obtained. Insights on the preference modeling paradigms combination with potential advantages for the decision process are also discussed in this paper.

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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.

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ABSTRACT In various Multi-objective Programming (MOP) problems, decision-makers are often faced with a large set of efficient solutions, presenting a challenge in discerning and selecting the best solutions within this broad set. To overcome this, decision-makers can tune and optimize their preference function over this efficient set to identify the optimal solutions that align with their preferences. Most existing methods address such problems in the deterministic case, while we aim to tackle a new challenge by dealing with these problems in a stochastic environment, which increases their complexity. Indeed, we focus in this study on proposing an exact method to optimize two preference functions over the efficient set of a Multi-objective Stochastic Integer Linear Programming (MOSILP) problem in order to find the best compromise solutions without enumerating all elements of this efficient set. The proposed method is based on the combination of two techniques: the first one is called the L-shaped method, while the second one is an adaptation of the branch-and-bound strategy by reinforcing it with efficient cuts and tests, which allows the method to remove a large number of inefficient solutions within the search tree. Moreover, the method exhibits adaptability in addressing the general case involving multiple preference functions. A didactic example is presented for illustration, followed by a computational study evaluating the method’s efficacy and performance by solving randomly generated instances.

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ABSTRACT This paper proposes a multicriteria model for ranking the functioning of the dominant economic sectors of the Mexican economy. The paper presents a real case study dealing with comparing economic sectors. It includes the problem situation, a suitable problem formulation, and a detailed version of the multicriteria evaluation model. The model considers the multiple dimensions involved in the evaluation. Eighty-nine dominant economic sectors of Mexico represent the alternatives to be considered in the evaluation model. The problem statement is a relative economic comparison of such sectors under a multicriteria ranking purpose from the 2019 Economic Census data. The study found that the model could determine the degree of the overall appeal of an economic sector in contrast to others.

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ABSTRACT The temporal bin packing problem with fire-ups (TBPP-FU) is a two-dimensional packing problem where one geometric dimension is replaced by a time horizon. The given items (jobs) are characterized by a resource consumption, that occurs exclusively during an activity interval, and they have to be placed on servers so that the capacity constraint is respected at any time. For energy efficiency reasons, an optimal assignment shall minimize a weighted sum of the number of servers in use and the number of switch-on processes (so-called fire-ups) resulting from the selected configuration. The associated ILP formulations are typically large in size, so that, in the recent past, several model improvements have already been proposed in the literature. However, with only one exception, all these techniques do not address the quality of the LP bound which is another crucial factor for the size of the branch-and-bound trees generated during the solution process. To this end, we present a new class of valid inequalities, contributing to a stronger LP relaxation, and discuss their numerical benefits by computational experiments based on benchmark instances and new test sets. Remarkably, the new cuts also lead to theoretical results about the optimal value of the LP relaxation.

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ABSTRACT Public bidding is a Brazilian subject of great importance, being subject to control by the federal audit court, to prevent deviations and corruption. Even national legislation has undergone recent changes to make the use of this instrument more effective. In the public aspect, the bidding process goes through the determination of the need, the publication process, the choice, the contracting, and the post-contract period. Since some of the bidding modalities are exclusively based in “lowest price” and prevent the direct use of MCDA selecting the alternatives, this paper proposes using a combined approach, using MCDA and cognitive maps, to help in the determination of the bidding object. This approach is applied to a hypothetical situation, and the case study shows the convenience of its practical use in a real situation. The specific case is related to structural covering, using NBR15575 as a criteria definition subsidy. The study shows a contribution of cognitive maps to express the rationale according to legal principles and providing elements of the MCDA model. While FITradeoff supports the definition of the object, which is fundamental to avoid failures in the contracting process. The recent FITradeoff web version is used and the advantage of using the method is the reduction of decision-maker biases, increasing the transparency of the process.

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ABSTRACT We present a novel approach to the inverse data envelopment analysis (DEA) process, based on the slacks-based measure (SBM) model in the presence of undesirable outputs. In the first step, we determine the minimum undesirable outputs levels that a decision-making unit (DMU) can produce, according to the level of inputs and desired outputs, based on weak disposability. We then introduce counterpart (hypothetical) units corresponding to each DMU. In the second step, we determine the optimal level of inputs and outputs for the newly created units, based on the SBM model in the presence of undesirable outputs. We present two new criteria models based on the SBM model, to compare the efficiency of the newly created unit in the inverse DEA process with the original unit. We demonstrate that the efficiency scores obtained from these two models are equal. Using the SBM-based inverse non-radial DEA process, we can use all inefficiency slacks related to all input and undesirable output components in the inverse non-radial DEA process to estimate inputs and outputs simultaneously.

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ABSTRACT This paper describes the psychometric validation procedure for the creation of an Artificial Intelligence (AI) engine based on the theory of precision psychology and expert system-type machine learning algorithms. The focus is on individual coping strategies and the factor of reconciliation in victims of armed conflict in Colombia. A non-experimental methodology with a cross-sectional design was used, with a total of 363 participants. The results highlight that elements related to economic factors, individual condition, and political concerns in the victims explain the conditions required to generate a reconciliation process in the context of reintegrating into civilian life. It is concluded that the use of artificial intelligence enhances the process of psychological care by providing precision in the etiological information of the illness and the data, which enables discrimination between the health status, symptoms, and disease of the victims.

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ABSTRACT The main goal of this research was to identify personal and professional factors of train drivers which imply in the occurrence of accidents (denoted in this study as situations to non-compliance with procedures of the train driver consisting of unsafe acts that could cause major accidents) of a Brazilian logistics company related to accidentes in the period from 2014 to 2016. The research involved 348 drivers and some independent variables associated with each worker such as distances of removal (railway sections), driver’s age, working time (time working in the company), marital status, number of trips (number of train trips as a driver); months of work (months of work in the company) and total hours driving trains. Responses of interest are accident rates per work month and accident counts. Under a Bayesian approach, Beta and Poisson regression models were assumed in the presence of excess zeros. For the accident rate/months of work response, the covariates number of trips, posting distances and age showed some evidence of significant effects. For the response accident count, the covariate hours driving trains shows some evidence that it is a significant covariate. These results may be of great interest to rail logistics company managers to improve rail safety using some Bayesian modeling approaches in the presence of excess zeros.

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ABSTRACT The Flexible and Interactive Tradeoff (FITradeoff) multicriteria method was developed under the scope of the Multiattribute Value Theory (MAVT) to elicit preferences under a partial information perspective. The flexibility of this method has been recently enhanced by the combination of two paradigms of preference modeling in the decision process, namely elicitation by decomposition (ED) and holistic evaluation (HE), improving the preferences elicitation task in a sense that fewer elicitation questions are expected to be answered by the Decision Maker (DM) to find a recommendation for the multicriteria decision making (MCDM) problem. The combination of two preference modelling paradigms in FITradeoff is an innovative characteristic on MCDM methods which deserves further analysis on its implications for the practice of decision making, not yet investigated in previous works. Considering that, this work aims to evaluate the impact of conducting HE in FITradeoff in terms of the expected reduction of the number of questions (NQ) that shall be answered to obtain the problem results. To do so, a simulation study has been carried out, in which multiple criteria problems have been generated and solved by simulating different preferences profiles. Hypotheses on the reduction of the number of questions were formulated and tested for identifying the actual effect of two different types of HE in the elicitation process: selection of the best alternative and elimination of the worst alternative considering a previously defined subset. Besides, we also analyze the relationship between the HE effects and important variables of MCDM problems such as number of criteria (NC), number of alternatives (NA), and weights distribution patterns (WD). The results obtained show that holistic evaluation judgments have a significant impact on the reduction of effort made by the DM in the elicitation process, in a sense that the total number of questions reduces in a significant manner, considering either selection tasks or elimination tasks in HE.

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ABSTRACT Uncertainty and disruption can significantly impact supply chains, and risk response is a means to diminish or circumvent these challenges. Therefore, this investigation aims to assess lead time variability in the supply chain of active ingredients. The research proposes a decision-making process to evaluate lead time variability in the active ingredient supply chain of the Brazilian chemical industry. It adopts Game Theory and linear programming in its solution. The two major contributions of this study are as follows: first, it presents a procedure to assess lead time variability; second, it proposes a supply chain risk response framework to address the lead time variability problem. Supply chain and lead time variability are emerging areas that offer significant opportunities for exploration, one of which is to evaluate lead time variability from the multiple perspectives presented in this study, thereby contributing to the current literature through a real application.

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ABSTRACT This paper deals with the two-dimensional strip packing problem (2D-SPP) with the order/or multi-drop and vertical stability constraints. The existing exact algorithm that solves this problem is not able to provide optimal solutions on large instances in a reasonable amount of time. Hence, with a view to quickly obtain a physically stable packing of minimum height while satisfying the order constraint, the Biased Random-Key Genetic Algorithm (BRKGA) is combined with Bottom-Left-Fill (BLF) and Open Space (OS) heuristics. Both versions of the algorithm (BRKGA+BLF and BRKGA+OS) retrieved optimal solutions on many benchmark instances, consuming lesser computational time than the exact algorithm. A comparative study was also performed between the BRKGA, Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms on newly generated large instances. Moreover, the effectiveness of the BRKGA has also been checked on the classical 2D-SPP and two-dimensional orthogonal packing problem (2D-OPP) datasets.

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ABSTRACT Aggregate Production Planning (APP) aims at balancing the forecast demand for product families with the available production resources, thus allowing changes to be made in the system and the best action strategy to be found. APP decisions are strategic decisions for the organization, which take an intermediate time horizon which spans 12 months, in general. As different issues may influence business success, this kind of decision problem will take multiple objectives into account, when a strategic view is considered. Conflicts between objectives frequently increase the complexity of APP problems. In order to deal with this kind of problem, this paper proposes a multi-criteria decision model considering the five objectives related to manufacturing strategy, namely: quality, speed, dependability, flexibility, and cost. By applying a multi-objective optimizing model which considers the organization’s strategical objectives, and by using the NSGA-II algorithm, a subset of representative solutions of the Pareto Frontier is obtained, thereby enabling the application of the FITradeoff method. A multi-criteria method, such as the FITradeoff, assists Decision Makers (DMs) in choosing a production plan more suitable to their objectives. The results show that the FITradeoff method contributes to the evaluation of solutions by aiding the DM to consider a significant set of alternatives while at the same time reducing the cognitive effort that he/she needs to make.

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ABSTRACT The globally changing market has provided the customers with multiple choices for buying any product. During transportation, the unpredictable circumstances cause deterioration/damage to the goods. Also, there are factors like rising fuel prices and a need to reduce the carbon emissions which pose challenges in transportation of goods for industries. All these factors motivate the authors to propose Bilevel Fractional/Quadratic Green Transportation Problem with uncertain cost and multi-choice supply and demand parameters (BFQGMCTP). The innovation of this paper is that apart from delivering maximum quantity of goods, the intent is to minimize the cost of transportation, the deterioration cost during transit and the cost of carbon emission simultaneously. The present problem is solved using two different techniques and a comparative analysis for the two satisfactory solutions is exhibited. The methodology in this paper has been elaborated through a pragmatic example which is elucidated by a computing software.

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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.

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ABSTRACT This paper highlights the challenges and opportunities introduced by disruptive technology for organizations. The convergence of emerging technologies holds the potential to enhance logistics and supply chain decision-making through heightened automation. The paper aims to conduct a multi-criteria assessment of readiness for implementing disruptive technology in supply chain management. The proposed approach employs the multi-criteria decision analysis methodology to assess organizational readiness and technological readiness. The approach suggests a procedure involving an analysis of benefits, opportunities, costs, and risks. It prioritizes and ranks factors associated with both organizational and technological readiness for the implementation of disruptive technology in supply chain management. Additionally, it introduces a supply chain risk response framework to tackle challenges related to readiness. Supply chain management and disruptive technology are expanding fields that provide significant opportunities for exploration. One of these opportunities involves assessing readiness from multiple perspectives, as presented in this paper, contributing to the literature.

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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.

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ABSTRACT Diabetes represents a significant global public health challenge. Effective diabetes management depends on adopting nutrient-controlled diets. This paper proposes a multi-objective mathematical optimization model for crafting appropriate diets for individuals with diabetes and ensuring adherence to nutritional requirements. Integrating integer variables, the model prioritizes minimizing carbohydrate and lipid consumption, recognizing the inherent trade-offs between these objectives. Balancing these objectives is critical considering the potential adverse health effects of excessive fat intake. In addition, the model facilitates the structure of the meal-based diet and enforces dietary diversity, promoting patient adherence while meeting vital nutritional criteria for diabetes control.

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ABSTRACT The main goal of this study is to determine the relative efficiency of the application of Lean Healthcare, based on a set of Brazilian public hospitals, using Data Envelopment Analysis (DEA). The study methodology consisted of establishing na analysis of the efficiency of Lean Healthcare, comparing the hospitals that applied it before and after, establishing the time and displacement as inputs and value as output, expressed in number of hospitalizations, to simulate the development conditions of the Lean in health. For this, the non-oriented SBM-DEA model was used, simulating the conditions of the medical clinics of the established DMUs. As a result, it was possible to observe that the hospitals were all inefficient before the application of Lean and had na improvement in efficiency after the application, but only a part actually became efficient. Thus, it is concluded that a metric that aligns the development of the Lean Healthcare application with DEA may be interesting, given the possibility of improvement arising from the benchmarks for the group of hospitals that remained inefficient.

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ABSTRACT In Brazil, the National Institute of Colonization and Agrarian Reform (INCRA) encounters difficulties in agricultural land parceling. Manual methods often prioritize the geometric regularity of lots instead of a fair subdivision concerning soil quality and expected crop output. The problem of finding fair land subdivisions regarding the soil’s agricultural aptitude has been named the Territorial Organization in Agrarian Reform Projects and Environmental Planning Problem (PROTERRA). Besides soil quality, PROTERRA requires that subdivisions exclude permanent preservation areas and native reserves, and imposes constraints on minimal access to water bodies and roads and a maximal area assigned to each lot. This study presents the new version of the Territorial Organization of Agrarian Reform and Environmental Planning System (SOTER-PA), which leverages combinatorial optimization algorithms to solve PROTERRA. We present its features and resources taking the most known geographic information systems. This system can also be used for other problems in a land subdivision and environmental planning context.

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ABSTRACT The companies located in Açu Port in Rio de Janeiro, Brazil, like other maritime ports worldwide, face the problem of sea corrosion. To reduce costs and increase equipment availability, a study was conducted to determine the effects of atmospheric corrosion on the operations of an industry plant. The study used a multicriteria decision to prioritize preventive maintenance. The model was based on the AHP and Electre III methods, used to classify anticorrosive methods suitable for equipment with a history of operational failures over a period of approximately four years. One equipment and one structural part were identified for the work. The model recommended zinc galvanizing treatments as the most suitable alternative to prevent corrosion in the selected equipment. For structures, galvalume treatment was recommended. The methodology was implemented in the studied company, and it has been helping to improve operational results and financial performance.

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ABSTRACT This study investigates the logistics risk factors impacting Sivas, a strategically significant region in Turkey’s logistics network, especially within the Belt and Road Initiative (BRI) framework. Using the Best-Worst Method (BWM), the study analyzes nine main criteria and twenty-seven sub-criteria that can cause delays or disruptions in logistics activities. Data were collected from 15 logistics experts in Sivas through questionnaires and analyzed using Lingo 20.0 software. The analysis reveals that transportation risk is the most critical factor affecting logistics activities in Sivas, while organizational risks have the least impact. Specifically, accidents during transportation were identified as the most significant sub-criterion, whereas worker strikes were deemed the least significant. This study contributes to the literature by offering a detailed categorization and prioritization of logistics risks, providing actionable recommendations for mitigating these risks. Furthermore, it presents a transferable model applicable to other regions with similar logistical and economic profiles, offering valuable insights for policymakers and industry stakeholders.

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ABSTRACT This systematic literature review examines the application of hygiene and motivation factors in project, operational, and supply chain management. Pre-defined selection criteria were used on four research questions to identify seventy-nine relevant publications from the Web of Science Core Collection. The review begins with the first research question - the characteristics of the selected publications. The second question - hygiene factors: salary, working conditions, employee well-being, and interrelationships - are analyzed afterward. The third question highlights motivation factors - promotion, career enrichment, empowerment, and learning. In addressing the fourth question, matches between regions with the most common business practices were identified. Despite the comprehensive research, only six publications explored these four research questions. Most publications concentrated on project management, and only a few mentioned operational and supply chain management professions, pointing to gaps for future research. The research limitation of focusing solely on open-access publications for in-depth analysis suggests the need for broader studies.

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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.

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ABSTRACT Brazilian public universities are essential entities to foment technological and scientific development through the generation and transmission of knowledge; the existence of this environment is only possible through the capture, maintenance, and management of organizational resources. Ensuring the availability of such resources is a complex process. Regarding the management of infrastructure projects, the scenario is especially challenging. Considering this context, the main purpose of this article is to apply a multimethodology, based on Strategic Options Development and Analysis (SODA) and Soft Systems Methodology (SSM), to structure the problem of managing infrastructure projects in a Brazilian Public University, using data collected in a previous analysis to explore the perspective of key stakeholders. The decision-making relevant system was chosen to be detailed and explored. Results show that the proposed multimethodology was able to provide essential diagnosis for the decision situation, bringing three main levels of necessary facilitating intervention.

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ABSTRACT This study structures objectives and sustainable-development alternatives for the Amazon Forest, based on the Amazônia 4.0 project. Value-Focused Thinking and Value-Focused Brainstorming were adopted. Amazônia 4.0 presents a new paradigm for the rainforest development, emphasizing the sustainable use of the biodiversity with innovative technologies. The project’s strategic objective is to promote the standing-forest’s value, through four fundamental objectives: adding value to products, creating means for industrialization, developing local economy and empowering communities. Alternatives include local mobile bio-industries, certified products, and educational partnerships. Challenges identified involve reevaluating the traditional credit system, creating new public policies, engaging numerous stakeholders, and addressing the lack of infrastructure. The project is in line with the Living Amazon Vision, proposed by the Science Panel for the Amazon, and takes the form of an operational bioeconomy project (already being tested). This study’s methodology can be applied to other initiatives seeking sustainable development in ecologically valuable regions.

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ABSTRACT Vulnerable regions to drought require resource allocation to develop projects to combat low rainfall negative impacts. In this perspective, this study proposes a multicriteria sorting model to categorize municipalities affected by drought in order to allocate resources according to criticality. The proposed model is based on the FlowSort method for sorting municipalities into highly critical, moderately critical, and slightly critical levels to cope with drought. The model was applied in the Apodi-Mossoró river basin in Rio Grande do Norte, Brazil, for sorting 14 municipalities. The findings revealed that the public administration could effectively focus its resources on municipalities experiencing more severe drought conditions. Thus, the public administration can develop strategies, public policies, and actions in coping with extreme difficulty.

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ABSTRACT Natural disasters often affect communities that become unable to access vital items. Not infrequently, the profile and scale of disasters require the delivery of various types of material and vital items, gaining prominence in these contexts the launching cargo by aircraft. This study presents a mathematical ballistic launch model that incorporates the main random variables that influence the trajectory of the load, making it possible to conduct analyses to improve the accuracy of launchings. In this way, Monte Carlo Simulations were utilized to investigate the trajectory deviations as a function of certain combinations of controlled factors in the model. Based on these findings, a Response Surface method was implemented, enabling the development of flight profiles that minimize load deviations from a desired impact point on the ground.

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ABSTRACT School dropout has significant consequences for individuals and society, including increased crime, reduced productivity, and limited economic innovation. Identifying students at risk of dropping out is crucial. This paper aims to develop a logistic regression-based tool for predicting dropout in the state’s public schools of Espírito Santo, Brazil. We utilized students’ information, such as grades, school attendance, socioeconomic data, and others, provided by Espírito Santo State Education Secretariat and the National Institute of Educational Studies and Research Anísio Teixeira. Various regularization methods were employed. We compared three model specifications for students in the first year of high school in Espírito Santo using data from 2019 to 2022. The results indicated that the models could identify at-risk students satisfactorily, highlighting the effective use of available data by educational departments to identify potential dropouts. This tool can aid educators in creating targeted interventions to minimize dropout rates.

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ABSTRACT Rising demand for more efficient and higher-quality public services has challenged public managers to meet these expectations. Performance evaluation has emerged as a crucial management tool to enhance public services. Its application in specific functional areas, such as Supply Chain Management (SCM), holds the potential to mitigate the escalating healthcare costs. This study aimed to develop a performance evaluation framework for the supply chain management of a public teaching hospital, utilizing the Constructivist Multi Criteria Decision Aid methodology (MCDA-C). Through structured interviews with the hospital's administrative manager, 160 criteria across eleven domains were identified for assessing supply chain management performance. The resulting framework allowed for a comprehensive evaluation, yielding a score of 51.55%. Proposed enhancements are expected to boost the global performance from 51.55 to 76.25% when implemented. A literature comparison underscores the comprehensive and specific nature of this performance evaluation model, demonstrating its influence on the healthcare services provided.

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ABSTRACT The Brazilian Agricultural Research Corporation is a public research company, comprised of a central management structure and forty-three research centers. Given the recent dismissal of employees, due to retirement or to promoted layoffs, and the expected announcement of a recruitment to replace the staff, it is important to define how these vacancies will be distributed among its member units. This study proposes data envelopment analysis (DEA) models to allocate the vacancies to the company’s research centers, using Zero Sum Gains DEA (ZSG-DEA). We studied both production and performance modeling perspectives. Given the approaches adopted and the variables selected, the ZSG-DEA models generated allocation proposals in which all units are 100% efficient. This is the ideal scenario for a central management: maximum efficiency in the use of its resources.

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ABSTRACT This paper proposes a decision model for the distribution of two different types of activities in the Brazilian Federal Police, common and special investigations, which usually generate difficulties for the manager when identifying adequate personnel for each category of task. Rational abstractions from Game Theory were used, especially the Principal-Agent theory and Shapley's value, building a model that associates both techniques, combined with a multicriteria model to measure the policemen’s operational satisfaction. It innovates the model in the combination of concepts that guide the achievement of optimal points for managing teams, without the use of pecuniary benefits. Results were found that manage to balance the distribution of investigations and goals to be met by the police unit. It is necessary to continue the research, improving the development of methodologies for assessing the capabilities and preferences of the Agent with regard to familiarity with special investigations.

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ABSTRACT The study addresses decision-making under conditions of uncertainty regarding the development of public policies and sustainable development strategies in an urban region in Brazil. Based on the case study, a decision support framework for planning and prioritizing urban sustainable development strategies (SDS) under uncertainty conditions is developed. In the framework social, economic and environmental factors have been considered using a fuzzy multi-criteria comprehensive evaluation approach in order to analyze and select SDSs. Critical factors and sub-factors for SDS are identified with the active participation of a committee of experts and representatives from different sectors of civil society. As a result, a set of urban sustainable development strategies are prioritized using the Fuzzy VIKOR Method that will help local authorities to improve their decisions. The decision support-framework illustrates the combination and application of Operations Research Methods in solving a complex problem related to decision-making in public management.

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ABSTRACT The present study applies a decision spatial model, previously developed, for the case of evaluating human development in the counties of the state of Rio Grande do Norte. The factors that encompass social, economic, health, education and territorial aspects of the counties were evaluated. The model makes use of decision rules and identification of spatial clusters to analyze the grouping of cities with better and worse performances. Three analyses were performed obtaining approximate results, verifying the robustness of the model employed. Additionally, the results were compared with the Human Development Index of the counties. In the case of the present study, the compensatory effect was not observed when compared to the original index, and the referred effect arises due to the calculation method used. Furthermore, the practical implication signifies the opportunity to develop public policies associated with the criteria showing poor performance and to visualize spatial patterns existing in municipalities with the same classification.

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ABSTRACT Organ transplantation plays a significant role in the healthcare sector, offering hope to patients with chronic diseases and organ failure. However, the logistical aspects of organ transplants present significant hurdles, with inefficiencies leading to organ loss during transportation and fatalities while on the waiting list. In this study, the combined use of Qualitative System Dynamics and Data Envelopment Analysis is employed to investigate, map, and analyze the efficiency of organ transplant logistics across different Brazilian Federative Units. From the Causal Loop Diagram, five (three as inputs and two as outputs) variables were selected to assess the efficiency through an output-oriented Data Envelopment Analysis model considering constant returns to scale. The results highlight efficient/inefficient Units, offering benchmarks and targets for improvement. This integration of methodologies provides a comprehensive perspective, empowering informed and strategic decision-making in the development of effective public policies and optimal allocation of public resources, thereby enhancing precision and efficiency.

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ABSTRACT This article presents an analytical evaluation of the behavior of dengue in the city of Fortaleza/CE, throughout all the epidemiological weeks of years 2007 to 2021, considering only the influence of rainfall on the increase of dengue in the municipality. The high correlation between the two events is shown through graphs of the global percentages over time and cross correlation, which imply the emergence of dengue outbreaks from the 13th epidemiological week for two consecutive years (2012 and 2013), taken as an example of investigation. In addition, the study shows that the amounts of rain falling between the 5th and 9th epidemiological weeks indicate the beginning of dengue outbreaks with greater or lesser intensity. We confirm cross correlation using Ljung-Box and Shapiro-Wilk statistical tests between rain and dengue SARIMA curves we found for the period, meaning that the rain explains Dengue human cases up to four weeks before they happen, applying SARIMA models to both events. Finally, we also show, by using instantaneous increase measures along epidemiological accumulated weeks from years 2007-2019, the outbreak identification, to better indicate to health managers its presence.