Multi-criteria Method Research Articles

Predictive spatial analysis for a critical assessment of the preservation potential of Palaeolithic record in the Leiria region (central Portugal)

Predictive spatial analysis in archaeology refers to the use of geostatistical and computational techniques to assess the relationships between the distribution of archaeological sites and the environmental context. It is increasingly becoming an essential tool in scientific-academic research and rescue archaeology. In the interconnection between these two working contexts, this study aims to explore the advantages of applying an inductive approach, combining Geographical Information Systems (GIS) and geostatistical methods, to identify areas with different degrees of probability for the preservation of the Palaeolithic record in the lower valley of the Lis River (Leiria region, central Portugal). Topographic, hydrographic, geological, and geomorphological data were collected, processed, and integrated into a spatial database, using a GIS, to define the environmental conditioning factors. After applying a spatial multicollinearity procedure, slope, topographical position index, cost-weighted distance to access the watercourses, heat load index and lithology were chosen as input variables for the predictive modelling. Archaeological data, corresponding to the location of known Palaeolithic sites, were also retrieved from the official records. Three models were implemented using regression and multi-criteria methods; for Model 1 a Generalised Additive Model (GAM) was applied, while for Model 2 and Model 3 two distinct combinations of Probabilistic Frequency Ratio (PFR) and Analytic Hierarchy Process (AHP) were used. The spatial cross-tabulation between the obtained predictive maps and the location of the known Palaeolithic sites shows that all the models are acceptable. However, the combinations of PFR + AHP seem to evidence greater efficacy compared to the GAM. Model 3 offers the best performance (90%), followed by Model 2 (87%) and Model 1 (68%). Possible sources of inaccuracies in the input data and the spatial modelling results were critically discussed. Model 3 generated the most robust and reliable predictive prototype map. The maps produced can serve local and regional agencies as a complement and aid decision-making in public policies for spatial planning, and in the conservation/management of cultural heritage. These cartographic representations can provide quicker identification of areas of interest, for example, in the context of rescue archaeology, along with a substantial reduction in time and costs for project promoters, as well as helping in the environmental impact assessments.

Exploring Analytical Hierarchy Process for Multicriteria Assessment of Reinforced Concrete Slabs

The decision regarding which slab type should be used in a building is generally made by the structural engineer, considering structural efficiency and compatibility with the architectural design, as well as the costs related to the amount of material used in each option. Because of the technical responsibilities inherent to this specialty, the decision-making process neglects to encompass various other factors of consequence that influence the construction process. These considerations include productivity, the visual and aesthetic characteristics of the slab, waste generation, and thermal and acoustic comfort. This paper aims to develop a multicriteria method to assist stakeholders in selecting the most suitable structural system for slabs based on project needs and objectives. The study utilized the Analytic Hierarchy Process (AHP) and information from bibliographic research, expert opinion using the Delphi Method, and machine learning on a dataset of over 2000 previously constructed slabs to achieve this goal. The analysis showed that the conventional solid slab type was the top priority, followed by the two-way waffle slab, one-way waffle slab, solid flat slab, and waffle slab. Additionally, the proposed AHP method was effective in developing a decision-making model for companies and the construction sector.

A Centralized Multi-Criteria Method for Scheduling Tasks in a Cloud Computing Environment

Task scheduling determines the order of mapping tasks to virtual machines to meet objectives. In this paper, a batch mode heuristic method that is centralized, dynamic, and multi-objective has been presented for scheduling independent tasks with a deadline and belonging to several user levels, using the cloud elasticity in the public cloud environment. In this method, it has been intended to improve the objectives of makespan, deadline violation, total execution cost, and load balancing by considering the tasks’ prioritization based on the criteria of user level, deadline, task length, and selection of heterogeneous virtual machines according to processing power, workload and usage cost. The proposed method was simulated using the CloudSim tool. Besides, the method’s ability to achieve the mentioned goals has been evaluated in comparison with similar methods. The evaluation results, established on standard test data, show that the proposed method has a good performance in improving its objectives.

An integrated decision support framework for selecting envelope and AC systems in hot-humid climate

This paper aims to introduce a framework that applies life cycle cost (LCC)-based optimization, life cycle assessment (LCA) and multi-criteria decision-making (MCDM) methods for the selection of optimum envelope materials and AC systems for housing projects. A total of 37 selection criteria and 28 material alternatives were first identified through a comprehensive literature review and interviews with local experts. “DesignBuilder”, a computer simulation software, was used to conduct the LCC-based optimization and LCA for the identified alternatives. Furthermore, uncertainties and risk associated with the selected alternatives were computed using Monte Carlo simulation via the Crystal Ball software and Efficient Frontier analysis via the Excel Spreadsheets. The identified selection criteria were then prioritized and assigned with utility scores based on the analytical hierarchy process (AHP) and multi-attribute utility theory (MAUT) methods. Seven scenarios with different objectives were set for an existing case study. The implementation of the framework showed that when taken into account the application of multi-criteria methods, the highest saving combination of materials is selected by the framework. The validation process was carried out through conducting interviews with local experts based on the results obtained from real case project. The experts agreed that the proposed framework can be beneficial to the industry as it takes into consideration not only quantitative criteria, but also qualitative criteria that are important to owners and designers.

Understanding housing design in urban areas through adaptability and flexibility assessment

ABSTRACT Housing adaptability and flexibility are constant themes in scientific literature. Technological advancements and shrinking urban spaces have led to new design proposals in architecture. However, evaluating housing solutions and contributing to projects can be challenging. The main objective of this study is to develop a framework for evaluating housing adaptability and flexibility. The framework is based on Adaptability and Flexibility Indexes and is performed using BIM and Dynamo plugin. The indexes are calculated using Analytic Hierarchy Process (AHP). Adaptability and flexibility are mainly related to dimensions, hierarchy, and circulation of housing design. Additionally, the use of multi-criteria methods in architecture can aid in understanding the subject. It is important to note adaptability and flexibility must be worked together to achieve the maximum potential of housing.

Experimental Research on the Use of a Selected Multi-Criteria Method for the Cutting of Titanium Alloy with an Abrasive Water Jet.

The use of selected multi-criteria decision methods for the optimization of cutting processes by abrasive water jet methods is increasingly being used in industrial processes. This is due to the complexity of the processes and the need to reduce operating costs. Process optimization methods are available to support organizational processes including the design phase, quality assurance, production automation, and many more. This article presents the current state of research on the water-abrasive cutting process and the use of multi-criteria methods in optimizing this process. This article presents a detailed methodological study of the VIKOR approach to optimization, indicating the applicability conditions, assumptions, and limitations on the example of high-pressure abrasive water jet cutting of elements made of titanium alloy utilizing HPX garnet abrasive. As a result of the research conducted, the best input parameters of the cutting process for abrasive flow rate, pressure, and the traverse speed of the cutting process were determined. The achieved result is consistent with the assumption that the most favorable output parameters are the highest cutting depth and the lowest level of roughness.

Search for optimal shipping routes in the Arctic seas

A method for choosing optimal shipping routes and determining the conditions under which the Northern Sea Route can be used year-round is developed in the paper. The topic and purpose of the study are directly related to the tasks, the implementation of which is provided by the Development Plan of the Northern Sea Route, approved by the decree of the Government of the Russian Federation on August 1, 2022, confirmed by the financing program for the development and implementation of the digital board of the Northern Sea Route, approved by the Government in mid-January, 2023. The assessment of the current state of the network of shipping routes, navigation, hydrographic and hydro meteorological support, as well as the structure and composition of the Arctic icebreaker and transport fleet is given. The main factors affecting the implementation of the year-round navigation program in the eastern sector of the Arctic include severe ice conditions, unreliable forecasts of the ice situation, the lack of a sufficient number of icebreakers and transport vessels capable of overcoming thick ice fields in the Arctic shallow waters. Based on the results of the review of existing methods for determining safe and cost-effective shipping routes, the basic requirements for methods of choosing optimal routes in the waters of the Arctic seas have been developed. Using the method of multi-criteria evaluation of alternative routes according to a variety of safety criteria depending on the navigation period and the method of transport vessels navigation in ice is justified. A list of information necessary for implementation of the developed multi-criteria method for finding optimal routes and a list of the main stages of its implementation have been compiled. The results of testing the method of comparative evaluation of alternative routes using a set of simulation models are presented. Recommendations on the use of the developed method are given. The main directions of further research are determined.

Assessing Geological and Mining Condition Nuisance and its Impact on the Cost of Exploitation in Hard Coal Mines with the Use of a Multi-Criterion Method

This article presents the use of a multi-criterion Analytic Hierarchy Process (AHP) method to assess geological and mining condition nuisance in longwall mining operations in selected coal mines in Poland. For this purpose, a methodology has been developed which was used to calculate the operational nuisance indicator (WUe) in relation to the cost of mining coal in individual longwalls. Components of the aggregate operational nuisance indicator include four sub-indicators: the natural hazards indicator (UZN), an indicator describing the seam parameters (UPZ), an indicator describing the technical parameters (UT) and an environmental impact indicator (UŚ). In total, the impact of 28 different criteria, which formed particular components of the nuisance indicators were analysed. In total 471 longwalls in 11 coal mines were analysed, including 277 longwalls that were mined in the period of 2011 to 2016 and 194 longwalls scheduled for exploitation in the years 2017 to 2021. Correlation analysis was used to evaluate the relationships between nuisance and the operating costs of longwalls. The analysis revealed a strong correlation between the level of nuisance and the operating costs of the longwalls under study. The design of the longwall schedule should therefore also take into account the nuisance arising from the geological and mining conditions of the operations. Selective operations management allows for the optimization of costs for mining in underground mines using the longwall system. This knowledge can also be used to reduce the total operating costs of mines as a result of abandoning the mining operations in entire longwalls or portions of longwalls that may be permanently unprofitable. Currently, underground mines do not employ this optimization method, which even more emphasizes the need for popularizing this approach.

Prioritization of resources in cartographic work using multicriteria methods: AHP, AHP-Gaussian and AHP-TOPSIS-2N.

The objective of the present work was to test the application of multicriteria methods for prioritizing the technical activities of the cartography sector of a military institution that produces geoinformation, aiming at increasing efficiency in productive operations and in the effective allocation of available resources. In this attempt, the multicriteria decision support methods AHP, AHP-Gaussian and AHP-TOPSIS-2N were used. In 75% of the scenarios tested, the priority alternative was A2 (Cartographic Mapping of Force Interest). In all methods, the two alternatives with the lowest priority were A6 (Survey of Heritage Areas) and A3 (COTER Simulation). The sensitivity analysis and consultation with the specialist regarding his opinion on the results obtained, allow us to state that the methods are consistent and corroborate with the expectations of the specialist who acted in the decision-making process for the prioritization of the activities in question.

The carbon footprint of ambulatory gastrointestinal endoscopy.

Endoscopy is considered the third highest generator of waste within healthcare. This is of public importance as approximately 18 million endoscopy procedures are performed yearly in the USA and 2 million in France. However, a precise measure of the carbon footprint of gastrointestinal endoscopy (GIE) is lacking. This retrospective study for 2021 was conducted in an ambulatory GIE center in France where 8524 procedures were performed on 6070 patients. The annual carbon footprint of GIE was calculated using "Bilan Carbone" of the French Environment and Energy Management Agency. This multi-criteria method accounts for direct and indirect greenhouse gas (GHG) emissions from energy consumption (gas and electricity), medical gases, medical and non-medical equipment, consumables, freight, travel, and waste. GHG emissions in 2021 were estimated to be 241.4 tonnes CO2 equivalent (CO2e) at the center, giving a carbon footprint for one GIE procedure of 28.4 kg CO2e. The main GHG emission, 45 % of total emissions, was from travel by patients and center staff to and from the center. Other emission sources, in rank order, were medical and non-medical equipment (32 %), energy consumption (12 %), consumables (7 %), waste (3 %), freight (0.4 %), and medical gases (0.005 %). This is the first multi-criteria analysis assessing the carbon footprint of GIE. It highlights that travel, medical equipment, and energy are major sources of impact, with waste being a minor contributor. This study provides an opportunity to raise awareness among gastroenterologists of the carbon footprint of GIE procedures.

A fuzzy preference programming and weighted influence non-linear gauge system for mission architecture assessment at NASA

The selection of a mission architecture is complex due to conflicting and intertwined mission operation criteria. In addition, the uncertainties inherent in human exploration missions make the evaluation process more challenging. This study presents a combination of improved fuzzy preference programming (FPP) and weighted influence non-linear gauge system (WINGS) to efficiently and effectively weigh conflicting and intertwined decision criteria and prioritize mission architecture scenarios at NASA. The improved FPP determines the weights of decision criteria, and the WINGS method considers criteria interdependencies and evaluates the alternative mission architecture scenarios. A numerical example demonstrates the proposed approach’s performance compared to three multi-criteria methods. A case study at the Johnson Space Center shows the applicability and efficacy of the proposed approach.

Quantification of pharmaceuticals in hospital effluent: Weighted ranking of environmental risk using a fuzzy hybrid multicriteria method

An analytical method for quantification of seventeen pharmaceuticals and one metabolite was validated and applied in the analysis of hospital effluent samples. Two different sampling strategies were used: seasonal sampling, with 7 samples collected bimonthly; and hourly sampling, with 12 samples collected during 12 h. Thus, the variability was both seasonal and within the same day. High variability was observed in the measured concentrations of the pharmaceuticals and the metabolite. The quantification method, performed using weighted linear regression model, demonstrated results of average concentrations in seasonal samples ranged between 0.19 μgL−1 (carbamazepine) and higher than 61.56 μgL−1 (acetaminophen), while the hourly samples showed average concentrations between 0.07 μgL−1 (diazepam) and higher than 54.91 μgL−1 (acetaminophen). It is described as higher because the maximum concentration of the calibration curve took into account the dilution factor provided by DLLME. The diurnal results showed a trend towards higher concentrations in the first and last hours of sampling. The risk quotient (RQ) was calculated using organisms from three different trophic levels, for all the analytes quantified in the samples. Additionally, in order to understand the level of importance of each RQ, an expert panel was established, with contributions from 23 specialists in the area. The results were analyzed using a hybrid decision-making approach based on a Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, in order to rank the compounds by environmental risk priority. The compounds of greatest concern were losartan, acetaminophen, 4-aminoantipyrine, sulfamethoxazole, and metoclopramide. Comparison of the environmental risk priority ranking with the potential human health risk was performed by applying the same multicriteria approach, with the prediction of endpoints using in silico (Q)SAR models. The results obtained suggested that sulfamethoxazole and acetaminophen were the most important analytes to be considered for monitoring.

The Social Services Risk Index at Local Level: A Tool for Diagnosis and Decision Making

The COVID-19 pandemic has had a decisive impact on our society, generating both direct and indirect effects in a multitude of dimensions, beyond the purely health-related, which have conditioned people’s well-being and quality of life. The social services system has played an essential role in absorbing the consequences of these impacts on the most socially vulnerable population. Analysing the social impacts and monitoring the risks derived from the pandemic can favour the prevention of risk situations, adjust the resources of the social services system to changing social realities and facilitate the strategic decision-making process to mitigate or minimise the impacts of potential socio-annual crises or catastrophes. This article presents a methodological process, based on the HCVRA (Hazards, Capacity Building, Vulnerability, Risk Assessment) disaster management models, designed ad hoc with the aim of identifying, on the one hand, the social impacts of COVID-19 and, on the other hand, the areas with the highest social risk in the post-COVID scenario. The application of this methodological process has made it possible to configure a set of indicators based on public databases, defined by consulting experts and weighted by a panel of stakeholders through a multi-criteria method to obtain a territorialised risk index at the highest level of disaggregation of the available data, based on the dimensions of vulnerability, threat and resilience.

Technical, economic, and environmental analysis to define the conditions for the implementation of charge stations, a case study in the city of Azogues - Ecuador

Reducing environmental pollution caused by traditional mobility solutions, such as combustion vehicles, requires a deep dive into sustainable mobility. Consequently, promoting electric vehicles (EVs) constitutes a long-hanging fruit for establishing a route map for decarbonizing city mobility. Nevertheless, several tasks require urgent attention to allow EV technology to deploy in cities. For instance, optimal locations of charging stations for EVs by considering a multicriteria approach are urgently required. This work studies the most feasible alternatives for locating and implementing EV chargers (EVC) in Azogues, Ecuador. This study applies Promethee multicriteria method, considering three different location alternatives in the city and four criteria that will be divided into ten subcriteria for the analysis. First, the multi-objective function´s weighting factors were established using three weighting methods: equal weighting, point allocation, and critical weighting. Once the matrix of sub-criteria with their weights was established, Visual Promethee, which works with Promethee II, was applied to establish the optimal candidate site. The results of this optimization analysis indicate an optimal location for the EVC.

Evaluation of wind measurement methods for determination of realistic wind shear: A case study in Aksaray, Turkey

Wind energy has become a large and important market in Turkey. Wind resource assessment and hub height extrapolation are the most analyses during wind power plant development. Wind shear is a critical parameter for wind speed analyses in wind energy power plant projects. The study covered measurement analyses of LIDAR (Light Detection and Ranging) and wind measurement mast system data that were compared as common in literature. Then wind shear formation and analysis factors were realistically evaluated with the multi-criteria method first in the literature using wind speed, wind direction, WSC, roughness, turbulence intensity (TI) and correlation factor. Under 100 m measurements were extrapolated to 101 m and upper 101 m. The predicted 245 pieces of the data set by using power law and log law and the measured data set were correlated with an anemometer and the LIDAR measurements to figure out an efficient prediction method. 20 pieces of wind shear coefficients (WSCs) were calculated using mast-mast, LIDAR-LIDAR, mast-LIDAR and LIDAR-mast wind speed measurement. Then, these WSCs were applied and tested for various measured wind speeds and the instantaneous wind speed was predicted with WSC values. Simultaneously, the log law method was repeated for different roughness values and the ideal roughness value was calculated for the site specifications. These predictions provided specific information about the height of wind shear and TI height supported by LIDAR and anemometers. In comparing data estimated by the power-law and log-law methods with measurements, good and acceptable results were obtained with more than a 0.999 correlation coefficient.

Performance of Sustainable Alternatives Using an Integrated Multi-Criteria Method: Evidence from Brazilian Food Sector

Performance of Sustainable Alternatives Using an Integrated Multi-Criteria Method: Evidence from Brazilian Food Sector

Combined Framework of Multicriteria Methods to Identify Quality Attributes in Augmented Reality Applications

This study proposes a combined framework of multicriteria decision methods to describe, prioritize, and group the quality attributes related to the user experience of augmented reality applications. The attributes were identified based on studies of high-impact repositories. A hierarchy of the identified attributes was built through the multicriteria decision methods Fuzzy Cognitive Maps and DEMATEL. Additionally, a statistical analysis of clusters was developed to determine the most relevant attributes and apply these results in academic and industrial contexts. The main contribution of this study was the categorization of user-experience quality attributes in augmented reality applications, as well as the grouping proposal. Usability, Satisfaction, Stimulation, Engagement, and Aesthetics were found to be among the most relevant attributes. After carrying out the multivariate analysis, two clusters were found with the largest grouping of attributes, oriented to security, representation, social interaction, aesthetics, ergonomics of the application, and its relationship with the user’s emotions. In conclusion, the combination of the three methods helped to identify the importance of the attributes in training processes. The holistic and detailed vision of the causal, impact, and similarity relationships between the 87 attributes analyzed were also considered. This framework will allow the generation of a baseline for the use of multicriteria methods in research into relevant aspects of Augmented Reality.

The Impact of the Intuitionistic Fuzzy Entropy-Based Weights on the Results of Subjective Quality of Life Measurement Using Intuitionistic Fuzzy Synthetic Measure.

In this paper, an extended Intuitionistic Fuzzy Synthetic Measure (IFSM) with intuitionistic fuzzy (IF) entropy-based weights is presented. This method can be implemented in a ranking problem where the assessments of the criteria are expressed in the form of intuitionistic fuzzy values and the information about the importance criteria is unknown. One example of such a problem is measuring the subjective quality of life in cities. We join the debate on the determination of weights for the analysis of the quality of life problem using multi-criteria methods. To handle this problem, four different IF entropy-based weight methods were applied. Their performances were compared and analyzed based on the questionnaires from the survey concerning the quality of life in European cities. The studies show very similar weighting systems obtained by different IF entropy-based approaches, resulting in almost the same city rankings acquired through IFSM by using those weights. The differences in rankings obtained through the IFSM measure (and only by one position) concern the six cities included in the analysis. Our results support the assumption of the equal importance of the criteria in measuring this complex phenomenon.

A Strong Sustainability Paradigm based Analytical Hierarchy Process (SSP-AHP) method to evaluate sustainable healthcare systems

The recent studies signify the growing concern of researchers towards monitoring and measuring sustainability performance at various levels and in many fields, including healthcare. However, there is no agreed approach to assessing the sustainability of health systems. Moreover, social indicators are less developed and less succinct. Therefore, with this work, authors seek to map sustainable reference values in healthcare and propose a conceptual and structured framework that can guide the measurement of the social sustainability-oriented health systems. Based on a new multi-criteria method called Strong Sustainability Paradigm based Analytical Hierarchy Process (SSP-AHP), the presented approach opens the availability for systems’ comparison and benchmarking. The Strong Sustainability Paradigm incorporated into the multi-criteria evaluation method prevents the exchangeability of criteria by promoting alternatives that achieve good performance values on all criteria, implying sustainability. The research results offer insights into the core domains, sub-domains, and indicators supporting a more comprehensive assessment of the social sustainability of health systems. The framework constructed in this study consists of five major areas: equity, quality, responsiveness, financial coverage, and adaptability. The proposed set of indicators can also serve as a reference instrument, providing transparency about core aspects of performance to be measured and reported, as well as supporting policy-makers in decisions regarding sectoral strategies in healthcare. Moreover, the presented approach can be helpful while performing cross-national comparisons. Our findings suggest that the most socially sustainable systems are Nordic countries. They offer a high level of social and financial protection, achieving very good health outcomes. Furthermore, their social sustainability is safeguarded by balancing all identified values. On the other hand, the most unsustainable systems, located in central and eastern European countries, have a high level of unmet needs, experiencing shortages in the workforce and underfunding of healthcare. A key challenge for them is to achieve sustainability by increasing the share of public expenditure on health and limiting the substantial dependence on out-of-pocket payments.

Improvement of the sustainable olive mill wastewater (OMWW) management in the region of Sousse (Tunisia) via ArcGIS Software

In Tunisia, the evacuation of olive mill wastewater (OMWW) in storage tanks remains the most common way to manage this toxic effluent. Several environmental damages are registered due to the inappropriate locations of this OMWW tanks. Indeed, the storage tanks locations must be carefully selected where hydrogeological, environmental as well as socioeconomic criteria must be simultaneously considered. For this purpose, an integrated approach based on Geographic Information System (GIS), Global Positioning System (GPS) and multicriteria method (Analytic Hierarchy Process AHP) were developed to asses OMWW tanks sustainable management in Sousse region (Tunisia). The present paper consists to evaluate the current management of OMWW tanks in comparison with the existing standards. The results showed that most of the sites were not in the appropriate zone and did not meet the necessary standards and the minimum requirement to put in a storage tank, as expressed by the exclusion criteria. This strongly emphasizes the seriousness of the deteriorated environmental situation in the region. An awareness of these dangers that threaten public health and have some other associated risks is important. Hard work to resolve this situation is urgently required.