Multi-criteria Method Research Articles

Effects of Return Air Inlets' Location on the Control of Fine Particle Transportation in a Simulated Hospital Ward.

The COVID-19 pandemic has made significant impacts on public health, including human exposure to airborne pathogens. In healthcare facilities, the locations of return air vents in ventilation systems may have important effects on lowering airborne SARS-CoV-2 transmission. This study conducted experiments to examine the influence of different return air vents’ heights (0.7 m, 1.2 m, and 1.6 m) on the particle removal effects in a simulated patient ward. Three different ventilation systems were examined: top celling air supply-side wall return (TAS), underfloor air supply-side wall return (UFAS) and side wall air supply-side wall return (SAS). CFD simulation was applied to further study the effects of return air inlets’ heights (0.3 m, 0.7 m, 1.2 m, 1.6 m, and 2.0 m) and air exchange rates. The technique for order of preference by similarity to ideal solution (TOPSIS) analysis was used to calculate the comprehensive scores of 60 scenarios using a multi-criterion method to obtain the optimal return air inlets’ heights. Results showed that for each additional 0.5 m distance in most working conditions, the inhalation fraction index of medical staff could be reduced by about 5–20%. However, under certain working conditions, even though the distances between the patients and medical personnel were different, the optimal heights of return air vents were constant. For TAS and UFAS, the optimal return air inlets’ height was 1.2 m, while for SAS, the best working condition was 1.6 m air supply and 0.7 m air return. At the optimum return air heights, the particle decay rate per hour of SAS was 75% higher than that of TAS, and the rate of particle decay per hour of SAS was 21% higher than that of UFAS. The location of return air inlets could further affect the operating cost-effectiveness of ventilation systems: the highest operating cost-effectiveness was 8 times higher than the lowest one.

Brainstorm on artificial intelligence applications and evaluation of their commercial impact

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span lang="EN-US">A countless number of artificial intelligence applications exist in a wide range of fields. The artificial intelligence (AI) technology is becoming mature, free powerful libraries enable programmers to generate new apps using a few lines of code. The study identifies the applications that are the most interesting for a developer as far as profit is concerned. Some AI applications related to trading, industry, sales, logistics, games, and personal services have been considered. To select the most promising AI applications, multi criteria methods have been adopted. This brainstorm may be useful to inspire new born start-ups, willing to create viral apps/products. The paper wishes to be informative and light, for further information, a rich selection of publications and books is provided.</span></p></div></div></div>

A multicriteria evaluation methodology for assessing the impact of COVID-19 in EU countries

Our purpose in this paper is to develop an integrated multicriteria evaluation methodology for assessing the impact of COVID-19 in the 27 countries of the European Union. Initially, a specialized and comprehensive set of normalized criteria metrics that capture several dimensions of the pandemic, such as infection, mortality, recovery and testing rates, is carefully specified. Then, by means of a well-established and intuitive weighting system, which directly takes into consideration the experts’ preferences, the gravity of each criterion is determined properly. Next, two of the most popular multicriteria ranking techniques, i.e. the TOPSIS and the PROMETHEE II, are simultaneously exploited in order to derive and integrate the obtained evaluations. Moreover, the value of the suggested decision support system is enriched through the introduction of a novel element in the field of multicriteria analysis, i.e. the ‘2-dimensions evaluation plane’, a data visualization concept which provides rich information to the decision maker, by fruitfully blending the ranking results of the utilized multicriteria methods. The validity of the proposed approach is verified through an indicative illustrative application on Coronavirus data for the European Union countries, deriving a wide spectrum of insightful conclusions. Finally, the flexibility of the suggested framework is also stressed, since it can be fully customized, both in terms of the selected criteria and its weights, and run repetitively under a specific time-step frequency, according to the evolution dynamics and implications of the underlying pandemic.

Framework for Optimized Analysis of Waste Bioenergy Projects

Over the years, cities have undergone transformations that, invariably, overload and even compromise the functioning of an energy matrix dependent on increasingly scarce resources. The high demand for energy has challenged stakeholders to invest in more sustainable alternatives, such as bioenergy, which, in addition, helps to reduce the pressure for finite resources, enable the energy recovery of waste and contribute to the mitigation of carbon emissions. For these improvements to be successful, stakeholders need specific technological strategies, requiring tools, methods and solutions that support the decision-making process. In this perspective, the current work aimed to develop a framework optimizing the evaluation of waste bioenergy projects through the application of algorithms. Therefore, a literature review was carried out to select the algorithms and identify the sectors/areas and stages in which they are applied. These algorithms were then grouped into two sequential phases. The first targeted the evaluation of region, based on the type and supply of biomass, while the second sought to optimize aspects related to infrastructure and logistics. Both phases were concluded with the application of multi-criteria methods, thus, identifying the areas/regions with the greatest potential for implementing bioenergy projects. In general, it was observed that there are different algorithms and multi-criteria analysis methods that can be suitable in bioenergy projects. They were used to identify and select the regions with the greatest potential for bioenergy plant implementation, focusing on the type, quantity and perpetuity of biomass supply, to assess the operational efficiency of machines, equipment, processes and to optimize the logistics chain, especially the collection and transport of biomass. Thus, the joint work between the use of algorithms and multi-criteria decision methods provides greater assertiveness in choices, helping to identify the most viable projects and mitigating risks and uncertainties for decision-makers.

Walkable Cities: Using the Smart Pedestrian Net Method for Evaluating a Pedestrian Network in Guimarães, Portugal

Evidence for the benefits of walking has attracted the attention of researchers and practitioners and encouraged them to develop healthier and more sustainable walkable cities. Many methods and approaches have been developed to measure walkability; namely, by using land use attributes. This paper examines the transferability of the Geographic Information System (GIS) based multi-criteria method developed in the Smart Pedestrian Net (SPN) research project to evaluate the level of walkability in a pedestrian network in Guimarães, Portugal. The method involves the assessment of 19 built environment and streetscape attributes, which were scored by a group of experts following the analytic hierarchy process. The method proved to be efficient in evaluating the pedestrian network and in mapping walkability in the study area. Around 65% of the street lengths scored above 0.60, indicating that the overall pedestrian conditions are favourable, with the best performance criteria being those related to accessibility and street connectivity. The method also allowed for the identification of different levels of walkability within the study area and the lack of a pedestrian network of highly scored streets. According to the results, the SPN method could be replicated in other cities to evaluate walkability and could be a useful planning tool to support policies towards developing more walkable cities.

A Novel Approach to Multi-Provider Network Slice Selector for 5G and Future Communication Systems.

The Network Slice Selection Function (NSSF) in heterogeneous technology environments is a complex problem, which still does not have a fully acceptable solution. Thus, the implementation of new network selection strategies represents an important issue in development, mainly due to the growing demand for applications and scenarios involving 5G and future networks. This work presents an integrated solution for the NSSF problem, called the Network Slice Selection Function Decision-Aid Framework (NSSF DAF), which consists of a distributed solution in which a part is executed on the user’s equipment (for example, smartphones, Unmanned Aerial Vehicles, IoT brokers) functioning as a transparent service, and another at the Edge of the operator or service provider. It requires a low consumption of computing resources from mobile devices and offers complete independence from the network operator. For this purpose, protocols and software tools are used to classify slices, employing the following four multicriteria methods to aid decision making: VIKOR (Visekriterijumska Optimizacija i Kompromisno Resenje), COPRAS (Complex Proportional Assessment), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Promethee II (Preference Ranking Organization Method for Enrichment Evaluations). The general objective is to verify the similarity among these methods and applications to the slice classification and selection process, considering a specific scenario in the framework. It also uses machine learning through the K-means clustering algorithm, adopting a hybrid solution in the implementation and operation of the NSSF service in multi-domain slicing environments of heterogeneous mobile networks. Testbeds were conducted to validate the proposed framework, mapping the adequate quality of service requirements. The results indicate a real possibility of offering a complete solution to the NSSF problem that can be implemented in Edge, in Core, or even in the 5G Radio Base Station itself, without the incremental computational cost of the end user’s equipment, allowing for an adequate quality of experience.

To prefabricate or not? A method for evaluating the impact of prefabrication in building construction

PurposePrefabricated products are continually entering the building construction market; yet, the decision to use prefabricated products in a construction project is based mostly on personal preferences and the evaluation of direct costs. Researchers and practitioners have debated appropriate measurement systems for evaluating the impacts of prefabricated products and for comparing them with conventional on-site construction practices. The more advanced, cost–benefit approach to evaluating prefabricated products often inspires controversy because it may generate inaccurate results when converting non-monetary effects into costs. As prefabrication may affect multiple organisations and product subsystems, the method used to decide on production methods should consider multiple direct and indirect impacts, including nonmonetary ones. Thus, this study aims to develop a multi-criteria method to evaluate both the monetary and non-monetary impacts of prefabrication solutions to facilitate decision-making on whether to use prefabricated products.Design/methodology/approachDrawing upon a literature review, this research suggests a multi-criteria method that combines the choosing-by-advantage approach with a cost–benefit analysis. The method was presented for validation in focus group discussions and tested in a case involving a prefabricated bathroom.FindingsThe analysis indicates that the method helps a project’s stakeholders communicate about the relative merits of prefabrication and conventional construction while facilitating the final decision of whether to use prefabrication.Originality/valueThis research contributes a method of evaluating the monetary and non-monetary impacts of prefabricated products. The research underlines the need to evaluate the diverse benefits and sacrifices that stakeholder face when considering production methods in construction.

Similarity of TOPSIS results based on criterion variability: Case study on public economic.

In the real world, acceptance of a decision is conditional on the availability of a great volume of data. Selection of a suitable solution on the basis of this data represents a problem that multi-criterial methods (MCDM) are applied to. The issue of which of these should be favoured during their use involves a specification of the importance of the assessed criteria. The goal of the presented research is to quantify the differences (symmetry) in assessment using selected MCDM methods (Technique for Order of Preference by Similarity to Ideal Solution-TOPSIS), while applying an absolute and relative variability of the assessed criteria to a determination of their importance. The obtained results indicate that the order of the assessed subject (alternative) is not directly influenced by the method of determining the variability of the assessed criteria. We can also state that the degree of concurrence in the order of application of the TOPSIS technique, in combination with both approaches expressed by the Jaccard index, is relatively low.

A Hybrid MCDM for the Location of Urban Distribution Centers under Uncertainty: A Case Study of Casablanca, Morocco

In this article, the main subject is the problem of the location of Urban Distribution Centers (UDC) in an environment characterized by uncertainty. Thus, a decision support process based on fuzzy multi-criteria methods (F-MCDM) will be proposed as the solution. The CATWOE method is used for identifying the Stakeholders (PPs) concerned by the localization. Furthermore, direct interviews and the review of the literature help to enhance the decision criteria. The use of the F-SWARA method made it possible to weight the criteria by taking into consideration the opinion of the PPs. The F-ENTROPY method corrected the subjectivity of the weights given by the first method. The hybridization of the two is a first in the literature in this field and allows precise and realistic results. In the end, the different alternatives obtained by the F-VIKOR method are ranked. This approach was applied to the city of Casablanca, which is extremely impacted by the negative externalities of urban freight transport. The results of this study showed that zone four (AIN SBAA) is the best zone to implement the UDC in the city of Casablanca. The sensitivity analysis validated the robustness of the model.

Multicriteria method applied to rehabilitation planning in water distribution networks

Multicriteria method applied to rehabilitation planning in water distribution networks

Selection of promotional media with the integration of AHP Fuzzy and TOPSIS (case study in a study program)

Private universities need new students as one of the income to be able to run their operations. For that promotion needs to be done by them. When carrying out promotional activities, it is necessary to look at the availability of the budget, so it is necessary to be selective and choose the right promotional media and according to the budget. Selection of promotional media in addition to considering the budget, there are several criteria that must be considered, therefore the selection requires a multi-criteria method, one of which is TOPSIS. Initial weighting of the criteria for TOPSIS can be done with Fuzzy AHP, this method is used because it can overcome the fuzzy assesment when performing pairwise comparisons. So far, there are not many combined applications of Fuzzy AHP and TOPSIS in the selection of promotional media, so this research is expected to have a contribution to fill the gap. From the results of the study, it was found that the order of criteria that were important for the study program in the selection of promotional media were; cost, reach, audience fit and easy to apply. Meanwhile, the result of selecting the best promotional media for this study program was through social media

A new multi-criteria method based on DEMATEL, ANP and grey clustering for quality sorting of incoming cores in remanufacturing systems under epistemic uncertainty: a case study of heavy-duty equipment

A new multi-criteria method based on DEMATEL, ANP and grey clustering for quality sorting of incoming cores in remanufacturing systems under epistemic uncertainty: a case study of heavy-duty equipment

New multi-criteria method for evaluation of sustainable RES management

This paper introduces a new V-COMET method for assessing the sustainable management of renewable energy sources (RES) in European countries. The proposed method belongs to the multi-criteria methods and is free of significant shortcomings occurring in most Multi-Criteria Decision Analysis (MCDA) methods. The paper shows that the V-COMET method is characterized by high accuracy and has very limited computational complexity. The practical contribution of the paper covers the use of the developed V-COMET method in RES assessment. The practical research domain covers the evaluation of 30 European countries in respect of criteria provided by Eurostat (the statistical office of the European Union). Three evaluation models with high criteria details for comparison were proposed: model with KTOE, percentage, and TOE per capita data. Due to the practical potential of the model with data in TOE per capita based on the V-COMET method, full robustness and sensitivity tests of the country rankings were carried out, showing the wide practical possibilities of the proposed approach. Additionally, a methodological evaluation of the proposed V-COMET method was performed. For this purpose, the uncertainty was investigated, and the developed V-COMET method was benchmarked with the set reference MCDA methods. The results allow concluding that the proposed method shows very high accuracy.

Spatial Group Decision Support System to Facilitate Site Selection Negotiation Process, Reduce Decision-Maker Conflict, and Augment System Performance

The selection of a suitable land requires careful thought and several criteria must be taken into account to ensure a good decision. Typically, selection processes are based on face-to-face meetings. But this strategy focuses on simple predefined searches and selections according to some basic criteria, such as land price, etc. They do not take into account spatially explicit criteria and spatial analyzes relevant to a site selection process (for example, proximity to hospital). To overcome these limitations, the proposed system relies on the integration of four key concepts: a multi-agent system, a multi-criteria method, geographic and ontological information systems. The results of the implementation provide manageability of large data storage. Despite the large number of approaches integrating geographic information systems and multicriteria analyzes, their use, in practice, is limited because they lack data semantics. As a result, the concept of ontology which introduces the semantics of the proposed approach offers many possibilities in terms of the type of terrain.

Intuitionistic fuzzy decision support based on EDAS and grey relational degree for historic bridges reconstruction priority

Bridge management includes all actions in the life cycle of the bridge, to ensure its safety, stability, and functionality. Numerous problems have been identified that are primarily related to the organization of planning and the role of decision-making in the reconstruction of the historic pedestrian bridges. The planning process for the reconstruction of these bridges is crucial due to increased traffic load, poor condition, or damage to bridges. Some of these bridges are part of the cultural heritage, while some are unfairly neglected. The motivation for this research arose from the need to establish the priority for the reconstruction of historic pedestrian bridges to achieve their safety, stability, functionality, and cultural preservation. For this reason, a new decision support model based on intuitionistic fuzzy group decision-making to the multi-criteria analysis is created. The model combines multi-criteria method Evaluation Based on Distance from Average Solution and grey relational degree (GRD) with intuitionistic fuzzy theory. Three relevant decision groups of experts are formed, with the knowledge and expertise in the area of research problematic, establishing criteria for the evaluation. A new approach to the consistency of criteria weights is proposed. The intuitionistic fuzzy likelihood function is developed for the aggregation of bridge evaluations. Furthermore, GRD values are calculated to determine the reconstruction priority ranking of bridge for each decision group. The final ranking is defined by integrating Integer Linear Programming (ILP) and Ant Colony Optimization (ACO), determining spatial-functional, time, and financial constraints.

Multi-Criteria Decision-Making Approach for Analyzing Competency Model of Technology Managers

The economies of all the countries are growing with the passage of time. In order to promote the businesses in the global markets, technology managers/technical brokers play a key role such as in the optimal allocation of scientific and technological resources. The industrialization of scientific and technological achievements is also possible due to optimal utilization of resources and a balance between exports and imports. The technology managers should be competent enough to bridge the gaps between the resource requirements and the availability of the resources required to run the businesses smoothly. This paper is using multi-criteria methods for analyzing the qualities in the technical managers which can assist the managers to run the businesses in an efficient manner to compete in the global markets. The interviews and questionnaire are used to collect the primary data. The opinion of experts is also considered. Then, SPSS 22.0 statistical analysis software is used to analyze the reliability and validity of the factors considered in the questionnaire. Then by using statistical techniques, a quantifiable competency model of technology managers is constructed. The multi-criteria AHP (analytical hierarchical process) method is used to compare the competency characteristic indexes of each level in pairs and quantitatively describe their importance of the criteria. It also assigns weights to judge the importance of each competency characteristic index. Since the evaluation of technical managers’ competency will be affected by various factors as mentioned in the paper, the fuzzy comprehensive evaluation method is also used to transform the evaluation dimension to accurately evaluate the competency of the technical manager which assists to judge the effectiveness of model evaluation. The proposed method provides theoretical and practical basis for the selection, evaluation, and cultivation of technical managers. It provides accuracy in results by 94% by adopting the statistical techniques.

EVALUATING ECONOMIC FREEDOM VIA A MULTI-CRITERIA MEREC-DNMA MODEL-BASED COMPOSITE SYSTEM: CASE OF OPEC COUNTRIES

Economic freedom indicators create a beneficial and suitable guide and a crucial reference for investors, policymakers, lenders, and market researchers worldwide. In light of these indicators, the economic freedom performances of countries can be determined. The Heritage Foundation annually releases a ranked list of the country based on their performance in terms of fourteen economic freedom criteria with equal weights through a simple aggregation approach. According to an average-based aggregator, equal weight of economic freedom criteria and calculating rank of countries cannot be a completely reliable approach. Thus, this work establishes a composite index system in the form of a decision support system that employs the method based on the removal effects of criteria (MEREC) and the double normalization-based multi-aggregation (DNMA) to specify the economic freedom levels of the OPEC countries. MEREC obtains the importance weights of indicators without the interference of any stakeholder or decision-makers. Afterward, DNMA, as a novel ranking multi-criteria method, is applied to sort countries based on their performance against all economic freedom criteria. This is the first attempt in the literature to calculate the index of economic freedom utilizing an integrated multi-criteria decision support model. Whereas “investment freedom” is the most significant indicator of economic freedom, the UAE is in the best position in terms of economic freedom among OPEC countries. A fourphased sensitivity control is also performed so as to verify the robustness and usefulness of the developed decision tool.

THE SHADOW ECONOMY’S PHENOMENON AND ITS IMPACT ON THE DEVELOPMENT OF CORPORATE BUSINESS AND HOUSEHOLDS IN UKRAINE

The shadow economy, along with macroeconomic imbalances and limited resources, will become a key global risk for the next decade. Withdrawing cash flows from the shadow sector and directing them to the legal economy solves numerous political, social, and economic problems of a country. That's why assessing the level of the shadow economy and solving problems of legalizing cashflows in any country has theoretical and practical significance. The purpose of this study is to assess the level of the shadow economy in Ukraine and to identify the problems, which give rise to it in the context of new challenges of the crisis phenomena both in Ukraine and around the world. The paper presents a comprehensive study of the shadow economy phenomenon, examines the root causes of its occurrence. The specificity of the study consists in assessing the level of the shadow economy in Ukraine according to the existing methods, namely: the unprofitableness of enterprises “household expenses – retail sales and services”, electrical and monetary. According to the review of scientific works, it is necessary to use a comprehensive indicator of the shadow economy assessment. Thus, considerable attention is paid to deepening the methodological aspects of assessing the shadow economy based on multi-criteria methods. The result of the study is the calculation of the shadow economy's level, considering the shadow currency turnover, based on the fact that Ukraine is a dollar-dependent country. A large proportion of the capital withdrawal into the shadow circulation is associated precisely with currency fraud. The obtained results confirm that the legalization of currency cash turnover should be mandatory in the process of foreign exchange regulation's transformation in Ukraine. Achieving this goal is associated with the deregulation of the foreign exchange market and the banking sector on the basis of moderate liberalization, warning the country's economy against the deployment of credit booms, improving the institutional provision of financial intermediation, developing a full-fledged market for derivatives, harmonizing national legislation with the best world experience and international standards of regulation, supervision and reporting, continuous monitoring of public opinion on the actions of monetary authorities and the consequences of these actions for the welfare and economic stability of corporate business and households.

Comparative analysis between AHP and ANP in prioritization of ecosystem services - A case study in a rice field area raised in the Guadalquivir marshes (Spain)

Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are helpful multi-criteria methods used by the decision-makers to prioritize the ecosystem services provided to humankind by a natural area. Despite being the most common in this field, as it is the easiest and quickest method, AHP simplifies reality by distributing criteria as a hierarchy. As many ecosystem services are firmly connected, this simplification can alter the results owing to the inherent subjectivity of the decision-makers' judgments when completing the required pairwise comparisons. In contrast, ANP considers the relationships among criteria, drawing a complex network that can help in reducing subjectivity and uncertainty. This study aims to compare how both the methods deal with these possible biases. This study prioritizes the ecosystem services provided by a farming area in an internationally recognized wetland with various interconnected services. The case study was conducted in a rice field area raised in the Guadalquivir marshes located within the Doñana Biosphere Reserve in Spain. After applying both methodologies, the results conclude that AHP considerably overestimates the most abstract services. Generally, decision-makers overvalue cultural services as they are socially more visible than others, and in AHP, they are not compared directly with other elements. Additionally, when a problem impacts the production and many people are affected, AHP also magnifies its importance because it is in the limelight. Therefore, ANP is an efficient method when a study requires higher accuracy and coexists with intangible assets despite the benefits and drawbacks of each multi-criteria method.

The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America

This study aims to help managers develop a proper strategy and policy for their company’s future. After the global COVID-19 pandemic, developed countries decided to change their production and relocate and re-industrialize. The U.S.’s big electronics and automobile companies are not an exception to this rule. The lithium batteries are the main instrument of mobile phone and electric vehicles. The leading lithium battery supplier for the U.S mobile phone companies is China. Argentina, Bolivia, and Chile (in South America) have some of the largest lithium mines in the world; these countries are known as the lithium triangle. Among the 86 million tonnes of lithium resources worldwide, 49.9 million tonnes exist in this area. The researchers in this study surveyed the best country for constructing a battery for companies in the U.S. Because of the growth of electric vehicles and their use of the lithium battery, the world is facing astronomical prices for lithium. To emphasize this issue and help managers create good policy, this study combined multiple methods. The improved suitability-feasibility-acceptability (SFA) strategy is integrated with the Bayesian best-worst method (BBWM) and measurement of alternatives and rankings according to compromise solution (MARCOS) multicriteria methods to determine the best destination. For comparison, based on the SFA strategy, seven criteria are introduced: commercially viable reserves, national minimum wage, corporate income tax, accessibility to mining companies, accessibility to the waterway, population, and political stability index. The Bayesian BWM analysis reveals that the foremost factor is corporate income tax, whereas MARCOS’s findings indicate that Chile is the best country to construct the lithium battery industry. To verify the proposed approach, a comparison analysis also is performed.