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Additive manufacturing (AM) technologies have transformed manufacturing, by providing greater control over material deposition and consumption. Thanks to greater customization and their high strength-to-mass ratio, the AM of composite materials has significantly grown over the past few years. The main focus in this research area is improving printing precision and higher production rates. However, there is a lack of thorough analysis on the energy consumption of fused filament fabrication (FFF) machines for composite manufacturing, especially when associated with mechanical and economic aspects. We designed an experimental method, based on flow analysis for measuring the impact of temperature parameters on total cost, energy consumption, and tensile resistance of composite parts made by FFF. The user should be able to improve FFF efficiency regarding economic, energy, and technical aspects and obtain recommendations for setting up and using the machine. This study confirms that combining traditional economic and technical indicators (total cost and tensile resistance) with emerging energy indicators (specific energy consumption) can be successfully applied to additive manufacturing to provide an overview of printing parameters impact. Results are yielding information to support optimization investigations depending on the need and goal. For example, two tested parameter combinations that offer similar tensile properties (4% reduction in tensile resistance compared to the best combination) show a 20% difference with lower energy consumption. [ABSTRACT FROM AUTHOR]

Pharmaceutical industries in most developing countries with limited resources are expected to encounter several barriers while incorporating Industry 4.0 to transform into Pharma 4.0. With limited resources, a developing country must prioritize the barriers consider their impacts, and make a resource utilization plan accordingly. In this study, We employed a hierarchical multiple criteria decision analysis (MCDM) technique to identify potential barriers to Pharma 4.0 in developing countries and examine their effects to generate a prioritization inventory. Firstly, we extracted the likely barriers using a systematic literature study and used an expert opinion-based Delphi Method to choose the most pertinent barriers. Subsequently, we analyzed the correlation and influence of the selected barriers on each other by formulating a hierarchical multi-criteria model integrating Interpretive Structural Modelling (ISM) and the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). As an outcome, we found three distinct categories of the selected 12 barriers: Prominent (4 of 12), Influencing (5 of 12), and Resulting (3 of 12). The results of this study are intended to assist the government in developing a solid adoption strategy for Pharma 4.0 and supply chain strategists in ensuring optimum resource utilization by resolving the examined barriers during the deployment of Pharma 4.0. The study is the first of its kind to discover barriers to Pharma 4.0 adoption and create hierarchical correlations within the context of the pharmaceutical sector from the perspective of a developing country.

The synergy between Distributed Ledger Technologies, like blockchain technology and circular economy, can lead to economic, environmental, and social sustainability through protecting natural resources, optimizing processes, fostering system effectiveness, designing out waste, and also providing job opportunities. Nevertheless, industries and their supply chain need to consider several requirements for blockchain implementation to realize a circular economy. To achieve this goal, requirements for implementing blockchain technology in construction supply chain were prioritized based on circular economy attributes. For multiple-criteria decision analysis and making our preference decision, we employed the new-founded multi-attribute decision-making (MADM) method, the "Fuzzy Ordinal Priority Approach (Fuzzy OPA)." Under uncertainty conditions, this method can determine fuzzy weights of circular economy attributes and fuzzy scores of blockchain requirements using linguistic variables. The results obtained from the case study show that three high-ranked requirements for implementing blockchain are (1) developing circular economy attributes on platforms, (2) intra-organizational considerations, and (3) technological requirements and collaboration infrastructure. To discuss the circular economy, we used the ReSOLVE framework, consisting of six attributes "Regenerate, Share, Optimize, Loop, Virtualize, and Exchange." According to research findings, blockchain implementation can move the construction industry toward a circular economy through (1) regenerating environment, (2) optimizing systems performance, and (3) looping and circulating products. [ABSTRACT FROM AUTHOR]

The relationship with bike infrastructure is missing in the current examination of user perception, which places a great deal of emphasis on visual aesthetic quality or surveys. Italy is experiencing the great development of cycling infrastructures, and the related plans, in line with sustainability objectives, have the task of examining users in various aspects. The purpose of this study is to examine users' criteria based on perceptions of the landscape in the presence of cycling infrastructures and to analyze the current infrastructures and understand their alignment with sustainable plans. One of the multiple-criteria decision analysis (MCDA) methods based on fuzzy comprehensive evaluation (FCE) was utilized, and it entails identifying the factors that constitute an index and assessing the priority of these factors in relation to other components. The findings demonstrate that the primary variables are distinct aspects of the landscape that are objective. We discovered that these components perform better for urban than metropolitan sectors in this study, as we divided the scenarios into metropolitan and general (urban, suburban, and coastal urban) scenarios. [ABSTRACT FROM AUTHOR]

The trend towards high-performance residential buildings with new building regulations necessitates fundamental changes in the residential market, which is currently driven by low initial investment costs and dominated by weak innovative cycles. This change involves a difficult decision-making process that must consider the multiple and generally conflicting objectives regarding optimal retrofitting for residential buildings. This study aimed to develop an approach that would provide feedback about a building's energy and economic performance in relation to the decision-making process to ensure that the complex residence retrofitting process is more efficient. For this purpose, a performance-oriented decision support workflow is recommended for a typical multifamily apartment block within a hypothetical settlement context in Istanbul Province, which includes (i) an automated parametric energy simulation through the coupling of EnergyPlus and MATLAB® to determine differences between retrofit alternatives in relation to the building envelope, energy systems and renewable energy systems, and (ii) a multiple-criteria decision analysis to determine the retrofit alternatives by which the optimal performance can be achieved, taking into account the conflicting nature of key performance indicators (primary energy saving and life-cycle cost saving). Architects and residence owners—who are the main decision makers—can use this proposed workflow to explore effective retrofit alternatives and to make informed decisions about performance-based retrofitting by comparing the energy and economic performance of these alternatives. [ABSTRACT FROM AUTHOR]

The harmonious interaction between humans and the biosphere determines how sustainable existence and coexistence are. However, when social challenges appear, sustainability is heavily compromised. Health is one of the areas affected by such challenges, with the delivery of health services being ensured by health systems. Consequently, understanding how sustainable health services are, especially those that consume the majority of resources—hospitals—is indispensable for a sustainable future. For this reason, we propose using a hybrid data envelopment analysis (DEA) approach to study hospital sustainability in Portugal under environmental, social, and economic perspectives, in cooperation with the Portuguese Ministry of Health. In particular, the proposed methodology incorporates the preference information of decision makers (via the construction of utility scales and the determination of Möbius coefficients) and criteria interactivity, due to the integration of the Choquet multiple criteria preference aggregation model in the DEA approach. In the end, despite approximately 30% of the sampled 29 assessed hospitals were deemed as efficient across the three perspectives in 2018, only 1 was entirely sustainable. [ABSTRACT FROM AUTHOR]

Managed retreat may be a necessity for coastal communities as sea levels rise due to climate change. Selecting the right policy decisions and timing is difficult given the vested interests of communities and stakeholder groups and requires careful balancing of the benefits and risks associated with each management alternative. State and federal agencies often employ single‐objective optimization frameworks such as cost‐benefit analysis to analyze coastal relocation alternatives, but such methods are limited in their ability to balance competing value considerations and stakeholder demands. The use of a multicriteria decision analysis (MCDA) methodology allows for such considerations to be quantified and evaluated, thereby improving planning and decision‐making for coastal retreat policies. This paper provides a strategic MCDA framework to evaluate coastal retreat policy that could be leveraged by at‐risk coastal communities. The MCDA is applied to a hypothetical coastal retreat scenario to visualize policy preferences and differing value considerations among stakeholders. This model can be used by government agencies to foster more sound, acceptable, and implementable coastal retreat policies and streamline the incorporation of this climate adaptation mechanism, which may be necessary for the near future. Integr Environ Assess Manag 2023;19:83–98. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS: This paper presents a multicriteria decision analysis tool that can assist in the development and evaluation of coastal retreat policy and decision‐making, and demonstrates the tool's functionality in a hypothetical coastal retreat scenario. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) technologies have transformed manufacturing, by providing greater control over the material deposition. Owing to its versatility and high strength-to-mass ratio, AM with composite materials has grown exponentially, founding many applications in industries. Further implementation of AM with composite materials would require the user to be able to improve FFF (Fused Filament Fabrication) efficiency regarding energy and technical aspects. For this purpose, it is necessary to assess the energetic and mechanical effects of printing parameters. In this paper, five printing parameters are evaluated: bed heating strategy, bed temperature, nozzle temperature, layer thickness and deposition speed regarding energy consumption during printing phase and ultimate tensile strength (UTS). A decision-making tool based on Ashby's material selection tool is also implemented to further discriminate different solutions. Different weights and a Pareto front have been used to illustrate the methodology's potential. Among the tested parameters, bed heating strategy has proven to be the most impactful parameter while bed temperature shows little to no effect. This study proposes a methodology as starting point for efficient FFF printing. [ABSTRACT FROM AUTHOR]

In the context of the multiple-criteria decision aid (MCDA), several fuzzy integrals concerning capacities (non-additive measures) have been introduced by various researchers in the last sixty years. Recently, Lehrer has proposed a new integral for capacities known as concave integral. The concave integral is based on the decomposition of random variables into simple ingredients. The concave integral concerning capacity is defined as the maximum value obtained among all its decompositions. The paper aims to model a new integration based on the decomposition of random variables into simple ingredients for multi-criteria decision making support when underlying scales are bipolar. This paper proposes a generalization of the concave integral in terms of decompositions of the integrated function to be suitable for bipolar scales. We show that the random variable is analyzed as a combination of indicators, where each allowed decomposition has a value determined by the bi-capacity. Lastly, we illustrate our framework by a practical example.

The studies on complex business issues in management described by multiple characteristics (indicators), use a variety of methodological approaches. Diverse decision support methods are used to solve problems in this area (depending on the situation considered). These methods include TOPSIS and VMCM. There are methodological similarities between them, but there are also several differences. VMCM eliminates some limitations of TOPSIS regarding, inter alia, the inclusion of non-typical objects, real-world patterns, and time-varying dynamics. Methodological considerations supplemented with an exemplary application are presented in this paper. [ABSTRACT FROM AUTHOR]

The relationship with bike infrastructure is missing in the current examination of user perception, which places a great deal of emphasis on visual aesthetic quality or surveys. Italy is experiencing the great development of cycling infrastructures, and the related plans, in line with sustainability objectives, have the task of examining users in various aspects. The purpose of this study is to examine users’ criteria based on perceptions of the landscape in the presence of cycling infrastructures and to analyze the current infrastructures and understand their alignment with sustainable plans. One of the multiple-criteria decision analysis (MCDA) methods based on fuzzy comprehensive evaluation (FCE) was utilized, and it entails identifying the factors that constitute an index and assessing the priority of these factors in relation to other components. The findings demonstrate that the primary variables are distinct aspects of the landscape that are objective. We discovered that these components perform better for urban than metropolitan sectors in this study, as we divided the scenarios into metropolitan and general (urban, suburban, and coastal urban) scenarios.

Objectives: This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies., Method: Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494)., Results: The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples., Conclusions: A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

The trend towards high-performance residential buildings with new building regulations necessitates fundamental changes in the residential market, which is currently driven by low initial investment costs and dominated by weak innovative cycles. This change involves a difficult decision-making process that must consider the multiple and generally conflicting objectives regarding optimal retrofitting for residential buildings. This study aimed to develop an approach that would provide feedback about a building’s energy and economic performance in relation to the decision-making process to ensure that the complex residence retrofitting process is more efficient. For this purpose, a performance-oriented decision support workflow is recommended for a typical multifamily apartment block within a hypothetical settlement context in Istanbul Province, which includes (i) an automated parametric energy simulation through the coupling of EnergyPlus and MATLAB® to determine differences between retrofit alternatives in relation to the building envelope, energy systems and renewable energy systems, and (ii) a multiple-criteria decision analysis to determine the retrofit alternatives by which the optimal performance can be achieved, taking into account the conflicting nature of key performance indicators (primary energy saving and life-cycle cost saving). Architects and residence owners—who are the main decision makers—can use this proposed workflow to explore effective retrofit alternatives and to make informed decisions about performance-based retrofitting by comparing the energy and economic performance of these alternatives.

Social vulnerability is deeply affected by the increase in hazardous events such as earthquakes and floods. Such hazards have the potential to greatly affect communities, including in developed countries. Governments and stakeholders must adopt suitable risk reduction strategies. This study is aimed at proposing a qualitative multi-hazard risk analysis methodology in the case of combined seismic and flood risk using PROMETHEE, a Multiple-Criteria Decision Analysis technique. The present case study is a multi-hazard risk assessment of the Ferrara province (Italy). The proposed approach is an original and flexible methodology to qualitatively prioritize urban centers affected by multi-hazard risks at the regional scale. It delivers a useful tool to stakeholders involved in the processes of hazard management and disaster mitigation. [ABSTRACT FROM AUTHOR]

Value in drugs do not always lies simply in them curing diseases: they may also be used to prolong life, improve its quality, and relieve patients' families. How much these elements matter should weigh on reimbursement decisions. Rare diseases often lack strong clinical evidence; hence, overlooking other elements that society values may lead to suboptimal decisions. We examine the preferences for treatments of non‐oncological rare diseases among 16 experts in Poland with PAPRIKA—a choice‐based elicitation method. Among seven attributes, clinical effect was found to be the most important, followed by returning the patient's family to normal functioning. Whether a treatment is used in children or any alternative treatment is available were the least important attributes. The respondents have a non‐linear, diminishing preference for clinical effects, and an almost linear (negative) preference for cost. We develop a new method of sensitivity analysis that accounts for the non‐uniqueness of part‐worth utilities and the possibility of respondents answering inattentively to some questions, and we find our results to be robust. When looking at heterogeneity, three types of respondents deviating from mean‐preferences emerge, in terms of what particular factors they place emphasis on: (a) cost and effectiveness, (b) to whom technology is offered (prognosis and availability of alternative), (c) the impact on family, safety, and caring for children. The part‐worth utilities identified can be used to support multiple criteria decision‐making in Poland. [ABSTRACT FROM AUTHOR]

Integrated planning and informed decision-making require an understanding of the interactions between coastal and rural social-ecological systems and quantification of the impacts of adaptive management across sectors. The Mar Menor lagoon (SE-Spain) provides an example of how a lack of integrated planning can lead to environmental and socio-economic crises. Here we present a systems approach using participatory modelling to identify optimal solutions for the sustainable development of this social-ecological system. Through a participatory process, we co-developed causal loop diagrams that formed the starting point of a System Dynamics model. Model development and its application helped facilitating knowledge exchange between stakeholders, identify challenges and opportunities for sustainable development, and evaluate the socio-economic and environmental impacts of different management and policy solutions. Model results were evaluated using multi-criteria analysis demonstrating its potential application as a decision support system to identify an optimal set of solutions. • Lack of integrated planning in coastal-rural areas hinders sustainable development. • Participatory modelling facilitates knowledge exchange among stakeholders. • System dynamic models allowed quantifying impacts of co-created solutions. • Multicriteria decision analysis helped identify an optimal set of solutions. • Participatory modelling facilitated system understanding and better-informed decisions. [ABSTRACT FROM AUTHOR]

Assessment of land suitability is a prerequisite for the conservation and maintenance of land productivity and the improvement of land use and management systems. This study assessed land suitability for rapeseed (Brassica napus L.) production using topography, climate, and soil data by analytical hierarchy process (AHP) and the Mamdani Fuzzy Inference System (MFIS). The study area covers 3737 km2 of land in the Diyarbakir province of southeastern Turkiye. The weights of topography, soil and climate factors in AHP were determined by expert opinions and the information in related literature. They were included in the whole process, mainly membership functions and rule base stages in the MFIS. The highest weighted factor was slope (0.264), followed by altitude (0.121), annual average temperature (0.114) and soil texture (0.112). The MFIS-based land suitability assessment indicated that the proportions of moderately (S2), marginally (S3) and currently not suitable (N1) land classes in the study area were 71.35%, 18.75% and 9.9%, respectively. The AHP results showed that 98.94% of the land was S3, and 1.06% was N1. The compatibility of AHP and MFIS methods in N1 land units was 96.05%, while the agreement for S2 and S3 land classes was not sufficiently high. The suitability of rapeseed cultivation has been more sensitively assessed by the fuzzy continuous classification obtained by the MFIS method. • Boolean logic separated moderately suitable land units according to distinct boundaries and ignored gradual transition zones. • Fuzzy logic-based land suitability assessment determines the membership degree of factors in sustainability classes. • Fuzzy logic approach generates precise land suitability classes, reflecting agricultural productivity. • Fuzzy logic provides optimal solutions in complex decision-making under uncertainty. [ABSTRACT FROM AUTHOR]

Solar power plants are important alternatives to fossil fuel-based power plants because they reduce greenhouse gas emissions and mitigate the effects of climate change. The potential of harnessing solar energy is highly dependent on selecting the optimal locations for plant installation. This study primarily aims to select optimal sites for solar energy plant installation using the Analytic Hierarchy Process (AHP) of Multi-Criteria Decision Analysis (MCDA) in a Geographic Information System (GIS) environment. In the underlying processing phase, the AHP method was used to calculate the relative weights of the study area's physiographic, utility, and climate data. These weights were then used in the MCDA to identify the optimal locations for solar plants. The results of the MCDA were presented in the form of a solar plant suitability map, which showed that 44.59 % (66506.49 km2) of the study area in the south and southwest of Bangladesh is highly suitable for the development of utility-scale solar power plants. In contrast, there are substantial areas of about 31.18 % (46507.37 km2) of the country where the installation of any type of power plant is completely prohibited. This research can help authorities and stakeholders decide where to invest in solar energy. [ABSTRACT FROM AUTHOR]

Public works in general play an important role because of their expressive value and considerable social relevance. In this respect, it is necessary to establish criteria/indicators for defining the hierarchy of works that must be conducted by a public entity, mainly for works considered ordinary, that is, those that do not stand out from a set of alternatives by degree of emergency or importance. Specifically, the hierarchization of engineering works to be carried out by the Public Administration in Brazil usually adopts the political approach to decision making without the application of rational technical criteria. Therefore, the aim of this article is to present a methodology to define the hierarchy of engineering works with the judiciary branch of power through the creation of technical criteria/indicators, followed by the application of the Fuzzy-Delphi technique to define the indices/weights that comprise the indicators. The technical criteria were created based on Resolution 114 of the country's National Council of Justice (Conselho Nacional de Justiça ; CNJ), whose weights were obtained through the aforementioned method, which was applied to a panel of experts, in two stages, with the adoption of triangular fuzzy numbers. The results, which were clear and objective, provide the General Hierarchization Index (GHI), with the ordering/ranking of the works included in the process. The methodology was validated in a case study applied to 162 alternatives (districts), containing 192 buildings of the Court of Justice of Paraná State (Tribunal de Justiça do Paraná ; TJPR), proving to be an important tool to support decision making. The optimization of resources through the determination of priorities converges to the sustainable hiring applied to public contracts. Institutions of the other Powers of the Republic could and should also be encouraged by public authorities to conduct technical studies similar to the proposal presented here, always clarifying the need for a clear and objective definition of the criteria and weights to be applied in the development of solutions for multicriteria decision making. • Public administration usually adopts the political approach to decision making. • It is necessary to establish indicators for defining the hierarchy of public works. • Fuzzy-Delphi technique is applied to define the indicators' indices. • A General Hierarchization Index ranking the public works. • The methodology was validated in a case study applied to 162 districts. [ABSTRACT FROM AUTHOR]

In the past decade, the use of multiple-criteria decision analysis technology has dramatically increased in solving complex real-world problems in solid waste management. Likewise, many municipalities have paid attention to finding feasible solutions for disposal and recycling of solid waste due to the increase in waste generation rates worldwide. Therefore, policy-makers must determine which recycling program to be implemented among various recycling program options. In this paper, a new approach to select a recycling program for recovered paper and pulp recyclables was proposed using analytic hierarchy process–Technique for Order Preference by Similarity to Ideal Solution (AHP-TOPSIS) techniques. A set of essential parameters of the decision-making system were identified, and a numerical case to illustrate the procedure was conducted. Our findings show very encouraging results to use a combined model between AHP and TOPSIS to select a suitable recycling program for different recovered recyclable materials. [ABSTRACT FROM AUTHOR]

This paper proposes a method for monitoring the structural health of concrete bridges in Iran. In this method, the bridge condition index (BCI) of bridges is determined by the analytical hierarchy process (AHP). BCI constitutes eight indices that are scored based on the experts' views, including structural, hydrology and climate, safety, load impact, geotechnical and seismicity, strategic importance, facilities, and traffic and pavement. Experts' views were analyzed by Expert Choice software, and the relative importance (weight) of all eight indices were determined using AHP. Moreover, the scores of indices for various conditions were extracted from experts' standpoints. BCI defines as the sum of weighted scores of indices. Bridge inspectors can examine the bridge, determine the scores of indices, and compute BCI. Higher values of BCI indicate better conditions. Therefore, bridges with lower BCI take priority in maintenance activities. As the case studies, the authors selected five bridges in Iran. Successful implementation of the proposed method for these case studies verified that this method can be applied as an easy-to-use optimization tool in health monitoring and prioritizing programs. [ABSTRACT FROM AUTHOR]

The whole interconnected European network is involved in the energy transition towards power systems based on renewable power electronics interfaced generation. In this context, the major concerns for both network planning and operation are the inertia reduction and the frequency control due to the progressive decommissioning of thermal power plants with synchronous generators. This paper investigates the impact of different frequency control constraints on the unit commitment of power plants resulting from market simulations. The market outputs are compared in terms of system costs, and of frequency stability performance evaluated on the basis of the rate of change of frequency and the maximum frequency excursion. The best compromise solution is found using a multiple-criteria decision analysis method, depending on the choice of the decision maker's weighting factors. The proposed approach is tested on a real case taken from one of the most relevant future scenarios of the Italian transmission system operator. The results show how the best compromise solution that can be found depends on the decision maker preference towards cost-based or frequency stability-based criteria.

Social vulnerability is deeply affected by the increase in hazardous events such as earthquakes and floods. Such hazards have the potential to greatly affect communities, including in developed countries. Governments and stakeholders must adopt suitable risk reduction strategies. This study is aimed at proposing a qualitative multi-hazard risk analysis methodology in the case of combined seismic and flood risk using PROMETHEE, a Multiple-Criteria Decision Analysis technique. The present case study is a multi-hazard risk assessment of the Ferrara province (Italy). The proposed approach is an original and flexible methodology to qualitatively prioritize urban centers affected by multi-hazard risks at the regional scale. It delivers a useful tool to stakeholders involved in the processes of hazard management and disaster mitigation.

Abstract In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. The K-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhouette index. The efficiency of each cluster of stations was determined using the Charnes, Cooper and Rhodes input-oriented data envelopment analysis model. A bi-objective zero one programming model was used to select a Pareto optimal combination of rank and distance of stations. The Pareto solutions for the presented bi-objective model were determined using the invasive weed optimization method. Although the proposed methodology is meant for the selection of repair and maintenance stations in an oil refinery Company, it can be used in multi-criteria decision-making problems.

Abstract: Due to the current climatic conditions and concerns about the energy generation by renewable sources, wind energy becomes an alternative to meet the existing energy demand. This paper aims to analyze the most promising regions of the State of Rio de Janeiro for the implementation of wind farms for electricity generation. As an analysis tool, we intend to use the Analytic Hierarchy Process (AHP), due to its practicality, to assist in the state’s wind power atlas regions evaluation, identifying generating farms installation feasibility based on logistical, technical and economic aspects. Three suitable regions for wind farms installation were evaluated according to the following criteria: potencial for generation, land cost, interconnection cost to the grid, implementing zones e terrain-landform logistics. It was found that, for the Serrana Region, it is indicated the installation of a wind farm that operates at 50 meters in height, because it only has enough potential for equipment with this height. In the Lakes Region, it is appropriate to use wind turbines of 75 meters in height, highlighting it as the most promising for this equipment height, besides having the best logistics capacity of the three regions. Because it has a greater potential area than the other, the North Region provides a greater total production, also taking into account its greater efficiency in the aerogenerators to 100 meters of height, considering this region as the most appropriate. It is worth highlighting that, in this region, there is potential for installation in all the heights presented, scrutinizing the results obtained.

The paper develops an analytical formulation that quantifies the effect of vertical grade on vehicle fuel consumption and then illustrates the use of the developed procedure in the identification of the fuel efficient freeway layouts. Specifically, the Virginia Tech Comprehensive Power-based Fuel consumption Model (VT-CPFM) was used to develop the formulation and then applied using 2015's 10 most-sold vehicles in the U.S. and Europe to quantify the vertical grade effect on vehicle fuel consumption rates. An increase in fuel consumption of approximately 140% was found when the roadway grade increased from 0.5% to 6%. The proposed selection procedure uses Geographical Information System (GIS) applications in the design phase to evaluate possible freeway layouts. A multi-criteria analysis is performed to rank the feasible alternatives. The yearly fuel consumed by cars traveling on each feasible layout is then predicted and the alternatives are sorted in ascendingly. If the alternative selected by the multi-criteria analysis gives the least yearly fuel consumption, then that alternative should be constructed. If not, then the alternative that results in the least yearly fuel consumption should be re-evaluated with respect to the one selected by the multi-criteria analysis tool. The proposed procedure is validated using a real case study involving the construction of a new freeway in Cameroon. As much as a 12% difference in fuel consumption was found between the alternative with the least estimated yearly fuel consumption and that selected based on a multiple-criteria decision analysis. [ABSTRACT FROM AUTHOR]