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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 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.