Multi-criteria Decision Analysis Methods Research Articles

Energy use in residential buildings for sustainable development: The fifth Solar Decathlon Europe revelations

This research focuses on achieving sustainable development in residential buildings with energy use. Under the influence of the energy crisis and related problems, research on residential buildings for less energy use has great potential. The literature review, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and including VOSviewer analysis, shows the research is increasing and meaningful. Solar Decathlon buildings are used as the main objects in this research. The fifth Solar Decathlon Europe energy use technologies are examined through onsite investigation and online searching. The Analytic Hierarchy Process method for multi-criteria decision analysis is used for sustainability assessment. Moreover, the Ladybug and ClimateStudio plugins simulated respectively the annual solar radiation and the best angle for receiving it. The main findings show that 34 kinds of technologies used in these buildings can be classified into two categories in three directions. Passive technologies should be applied and prioritized, but generating renewable energy is also important. Some infrequently used technologies are not insignificant. The research shows that the combination of technologies decides sustainability performance, but the quantity used does not. Furthermore, energy use also needs to be balanced and coordinated in combination with architectural aesthetics. This research on energy use in residential buildings is beneficial for achieving sustainable development.

Multi-Criteria Decision Analysis of an Innovative Additive Manufacturing Technique for Onboard Maintenance

Access to spare parts in the maritime industry is limited throughout most of a ship’s life cycle. The limitation is caused by both the geographical distance of vessels from suppliers and the often limited turnaround time during which parts can be delivered. Manufacturing some parts onboard is possible, but it is a time-consuming and labour-intensive process. Advanced manufacturing techniques could be used to improve access to spare parts at sea by combining the desirable materials properties and flexibility of Direct Energy Deposition (DED) and the higher dimensional tolerances of Computer Numerical Control (CNC) manufacturing. The present study assesses the comparative viability of onboard implementation of advanced manufacturing techniques for offshore assets as a capital investment in different modes against an option of no onboard advanced manufacturing using a multi-criteria decision analysis method. To this end, a Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) is employed considering the techno-economic and environmental aspects of the decision-making process as well as the inherent challenges that come with a new area of research. Finally, the challenges, opportunities, and pathways to onboard maintenance using additive manufacturing are discussed within the scope of the sustainable future for ship and offshore energy assets.

The application of multi-criteria decision analysis in gaining a premier sort of stability in airplane safety

Improving the aeronautical safety has been of high importance for the experts. Different factors influence the static and dynamic stability of the plane. These factors play important roles in the plane safety. The static and dynamic safety include several factors. Taking all the technical criteria and elements into account, this article tries to find a suitable method for evaluating and eventually deciding on the best alternative. One of the methods of multi-criteria decision analysis is the concordance analysis (CA) which is an important way of evaluation in solving issues of different miscellaneous criteria that cannot be incorporated into one another. Also, Best-worst method (BWM), one of the most practical decision-making methods, is used in this article. Using the CA and BWMs and based on different criteria, this research prioritises the premier stability alternatives and uses them in the design and finally suggests a suitable alternative out of the influential linear and lateral ones. To do this, a combination of extant varieties including 15 criteria and three alternatives is used and the concordance and non-concordance collections and criteria are defined. The results showed that in addition to the fact that the use of both methods led to the same results; as a result, the linear, lateral and directional became the best options for aeroplane safety, respectively, for design purposes.

A geospatial analysis of flood risk zones in Cyprus: insights from statistical and multi-criteria decision analysis methods.

Over the past few decades, flood disasters have emerged as the predominant natural hazard in Cyprus, primarily driven by the escalating influence of climate change in the Mediterranean region. In view of this, the objective of this study is to develop a geospatial flood risk map for the island of Cyprus by considering 14 flood hazard factors and five flood vulnerability factors, utilizing geographic information systems (GIS) and remotely sensed datasets. A comparative assessment was conducted for hazard mapping, employing statistical methods of frequency ratio (FR) and FR Shannon's entropy (FR-SE), and multi-criteria decision analysis method of fuzzy analytic hierarchy process (F-AHP). The main findings indicated that the FR method exhibited the highest predictive capability, establishing it as the most suitable approach for flood hazard mapping. Additionally, vulnerability factors were aggregated using F-AHP to generate the vulnerability map. The resulting flood risk map, which is the product of flood hazard and flood vulnerability, revealed that 9% of the island was located within highly risky regions, while 13.2% was classified as moderate risk zones. Spatial analysis of these high-risk areas indicated their concentration in the primary city districts of the island. Therefore, to mitigate future risks within these cities, an analysis of potential expansion zones was conducted, identifying the best-suited zone exhibiting the lowest risk. The generated flood risk map can serve as a valuable resource for decision-makers on the island, facilitating the integration of flood risk analysis into urban management plans.

Applying multi-criteria decision analysis in the bidding process of an own social security regime institute

Public administration is responsible for managing public resources and offering various types of services to the population. Therefore, to ensure that the maintenance of state bodies is carried out in a responsible manner, both for the acquisition of goods and for the contracting of services, it is necessary to carry out bidding processes that follow constitutional principles. In this way, the use of Multi-Criteria Decision Analysis (MCDA) methods can help decision makers to solve selection problems in public institutions. In this context, the objective of this paper is to select, from a pre-defined list of ten alternatives, the three cars considered most suitable to meet the needs of an Own Social Security Regime Institute, allowing the opening of a bidding process more reliable. To carry out this selection, three MCDA methods were used to aid the choice: Analytical Hierarchical Process (AHP), PROMETHEE II and Weighted Sum Method (WSM). The results demonstrated that the three methods applied together managed to select the three best cars for carrying out the bidding process and that the use of these tools has great potential for the area of public management.

Spatial Network Analysis of Coupling Coordination between Digital Financial Inclusion and Common Prosperity in the Yangtze River Delta Urban Agglomeration

Digital financial inclusion and common prosperity are pivotal elements in promoting the sustainable socioeconomic development of China. This study introduces a novel Multi-Criteria Decision Analysis (MCDA) method to evaluate the Common Prosperity Index (CPI). Using this index, alongside the Digital Financial Inclusion Index (DFII) released by Peking University, it examines the evolution of the coupling coordination relationship between digital financial inclusion and common prosperity within the Yangtze River Delta (YRD) urban agglomeration from 2011 to 2021. By integrating gravity models and social network analysis, in this paper, we thoroughly investigate the spatiotemporal evolution characteristics of the spatial network of this coupling coordination relationship. The results indicate that both the DFII and CPI generally exhibit an upward trend, but the decline in the coupling degree reflects a weakened interaction strength between them. Specifically, Anhui significantly lags behind Jiangsu, Zhejiang, and Shanghai in the development of digital financial inclusion and common prosperity, indicating regional development imbalances. Furthermore, the strength of spatial connections in city coupling coordination has significantly increased, with Nanjing’s siphon effect on cities in Anhui becoming markedly stronger, and the number of core cities in the network increasing, which demonstrates a geographical proximity feature in network development. Additionally, the overall network characteristics are transitioning towards higher density and “small-world” properties, suggesting a trend toward network stabilization. The disparity in centrality among cities has decreased, with an overall enhancement in centrality, where the spatial spillover effects from core areas such as Hangzhou-Ningbo, Nanjing-Changzhou, and Shanghai-Suzhou-Wuxi significantly promote the development of peripheral cities. Based on these findings, this paper proposes policy recommendations for the sustainable development of digital financial inclusion and common prosperity in the YRD region.

Assessing the relative contribution of various anthropogenic sources to atmospheric methane in Rivers State, Nigeria: A multi-criteria decision analysis approach

Methane is a significant greenhouse gas, with a global warming potential many times greater than carbon dioxide over a 20-year period. Its release from sources like landfills, agriculture, and the energy sector exacerbates climate change, making it crucial to monitor and reduce methane emissions to mitigate global warming and achieve climate goals. This research utilized the Multi-Criteria Decision Analysis (MCDA) method, specifically the Analytic Hierarchy Process (AHP), to analyze the sources of atmospheric methane in Rivers State, Nigeria. It addressed the challenge of assessing the contributions of various anthropogenic sources such as fossil fuels, landfills, agriculture, wetlands, and oceans to atmospheric methane emissions. By incorporating expert opinions, literature reviews, and surveys, the study constructed a hierarchical model to prioritize these sources based on their impact. Findings identified fossil fuels and landfills as the main contributors. The study demonstrated MCDA's effectiveness in environmental analysis and provided a replicable framework for similar assessments in other regions, contributing to targeted emission mitigation and policy formulation efforts.

Comparison of weighting methods of multicriteria decision analysis (MCDA) in evaluation of flood hazard index

Comparison of weighting methods of multicriteria decision analysis (MCDA) in evaluation of flood hazard index

Integrating structure time series forecasting and multicriteria decision analysis for adaptive operational risk assessment: an empirical study using real-time data

AbstractThis study propose a framework for integrating Multi-Criteria Decision Analysis (MCDA) and Structure Time Series (STS) prediction for multivariate operational risk assessment often with highly dynamic risk determinants. In particular, by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as an MCDA method, the framework is able to prioritize risk determinants according to their inherent uncertainties’ impacts on their respective operational objectives, and by employing Seasonal Autoregressive Integrated Moving Average (SARIMA) as an STS technique, the framework emphasizes real-time knowledge utilization for iteratively reducing uncertainty. By integrating SARIMA and TOPSIS, the framework aims to construct a multivariate operational risk assessment profile that is prioritized and continuously updated by the latest data and knowledge. Based on the proposed framework, the study constructs a mathematical model coded in Python to perform an empirical assessment of 161 countries’ operational risk using real-time data from the Armed Conflict Location & Event Data Project’s. A comprehensive analysis of the model’s functionality, quality, and sensitivity based on the assessment result is provided. Conclusions and limitations are also discussed, highlighting the model’s theoretical novelty and practical implications.

Multi-criteria decision analysis: technique for order of preference by similarity to ideal solution for selecting greener analytical method in the determination of mifepristone in environmental water samples

This work proposes the use of multi-criteria decision analysis (MCDA) to select a more environmentally friendly analytical procedure. TOPSIS, which stands for Technique for Order of Preference by Similarity to Ideal Solution, is an example of a MCDA method that may be used to rank or select best alternative based on various criteria. Thirteen analytical procedures were used in this study as TOPSIS input choices for mifepristone determination in water samples. The input data, which consisted of these choices, was described using assessment criteria based on 12 principles of green analytical chemistry (GAC). Based on the objective mean weighting (MW), the weights for each criterion were assigned equally. The most preferred analytical method according to the ranking was solid phase extraction with micellar electrokinetic chromatography (SPE-MEKC), while solid phase extraction combined with ultra-high performance liquid chromatography tandem mass spectrometry (SPE-UHPLC-MS/MS) was ranked last. TOPSIS ranking results were also compared to the green metrics NEMI, Eco-Scale, GAPI, AGREE, and AGREEprep that were used to assess the greenness of thirteen analytical methods for mifepristone determination. The results demonstrated that only the AGREE metric tool correlated with TOPSIS; however, there was no correlation with other metric tools. The analysis results suggest that TOPSIS is a very useful tool for ranking or selecting the analytical procedure in terms of its greenness and that it can be easily integrated with other green metrics tools for method greenness assessment.

Multi-criteria decision framework for catalyst selection: Production of formic acid as a circular liquid organic hydrogen carrier in the hydrogen economy

This study aims to use the multi-criteria decision analysis (MCDA) for the selection of suitable catalysts for the production of formic acid (FA), which serves as a circular liquid H2 carrier for the H2-carbon cycle. TOPSIS, VIKOR, ARAS, COPRAS, and PROMETHEE analytical decision-making methods were used to establish priority rankings for each method. With the exception of the top two ranks, the rankings differed across the methods. Therefore, we proposed an alternative ranking for the catalyst selection in the FA production, where all the methods’ results were given equal priority. By aggregating the outcomes from the decision methods and sorting them in ascending order, a final prioritized ranking was established. Our results showed that the proposed MCDA method was effective in identifying the most suitable catalyst for the FA production as a circular LOHC in the H2-carbon cycle. The model determined that Pd nanoparticle-based activated carbon-supported catalyst exhibited high activity, selectivity, and stability, while also being cost-effective. The findings of this study might contribute to the development of more efficient H2 storage systems based on FA.

A framework for evaluation of construction and demolition waste management alternatives using MCDA techniques in the context of Dhaka City

Landfilling and dumping are the common strategies to manage generated construction and demolition waste (C&DW) in Dhaka City. These strategies of C&DW management (C&DWM) affect the environment adversely and fill the old landfill sites quickly. Besides, there isn’t any framework to manage C&DWs effectively. This study introduces a Multi-criteria Decision Analysis (MCDA)-based C&DWM framework for Dhaka City by incorporating the expanded Waste Management Hierarchy (E-WMH). The E-WMH principles are considered as the C&DWM alternatives. Through a comprehensive literature review, the criteria are determined and grouped into social, economic, environmental, and technical criteria to achieve sustainability and effectiveness. To construct the initial decision matrix, the ordinal data (i.e. rating) is collected through interviews with the subject-matter experts of Dhaka City. Also, the ranking system method is used to determine the weight of the criteria. Finally, the ELECTRE I and ELECTRE II MCDA methods are employed to rank the alternatives. Results show that reuse and recovery are suitable strategies for managing C&DWs in Dhaka city. Future studies may consider the hybridization of MCDA tools, quantitative data to form the initial decision matrix, and other mathematical models to weigh the criteria so that the performance of the framework can be enhanced.

Multicriteria GIS-based assessment of biomass energy potentials in Nigeria.

The understanding of the geographical variability of biomass energy is an essential requirement for the optimal location of biomass energy conversion plants. This research presents a multicriteria GIS-based assessment of biomass energy potentials and the appropriate siting of biomass plants in Nigeria. The study applies the weighted overlay multicriteria decision analysis method. Crop and forest areas, settlement (energy supply areas), shrub/grasslands, barren land, water bodies, distance from water sources, road accessibility, topography, and aspect are the criteria that were considered for locating a biomass facility in this study. The results suggest that the theoretical, technical, and economical energy potentials of crop residues are highest in the North-East region of Nigeria and estimated at 1,163.32, 399.73, and 110.56PJ/yr, respectively, and lowest in the South-East at 52.36, 17.99, and 4.98PJ/yr, respectively. The theoretical, technical, and economical energy potentials of forest residues are highest in the North-West, estimated at 260.18, 156.11, and 43.18PJ/yr, respectively, and lowest in the South-East at 1.79, 1.08, and 0.30PJ/yr, respectively. Although most areas were identified to be suitable for siting biomass plants across Nigeria, the most suitable areas are located in the northern part of the country and include Niger, Zamfara, the Federal Capital Territory, Nassarawa, Kano, Kebbi, Kaduna, and Borno State. The study supports the Nigerian bio-energy policy that proposes to effectively utilize Nigeria's non-fuelwood as a substitute for the felling of trees. This is very important to strengthen its commitment at the COP26 International Climate Conference, which is to conserve and restore its forest. Furthermore, this study will serve as a good reference for policymakers to make well-informed decisions on tackling the energy insecurity in Nigeria.

Multi-criteria decision analysis applied to Brazilian grapevine genotype selection

Developing new table grape cultivars that exhibit high yield and superior fruit quality is imperative to meet the escalating demands of the consumer market in the Lower-Middle São Francisco River Valley. The primary objective of Embrapa Semiárido's Active Germplasm Banks (AGB) for grapes is the conservation of Vitis sp. germplasm under semi-arid climatic conditions to make it available for research, particularly for the breeding and development of novel grape cultivars. This study aims to use Multi-Criteria Decision Analysis (MCDA), specifically the Preference Ranking Organization Method for Enrichment Evaluation (Promethee) II, to rank the grape genotypes of the Embrapa Semiárido's AGB, considering multiple criteria to define the primary grape varieties for the breeding program. The decision maker (DM) participated in all process stages, from validating qualitative and quantitative criteria to evaluating the criteria weights, and the decision matrix had 106 seeded and 50 seedless grape genotypes with 14 criteria. For visual analysis, we generated the GAIA Plane using the Visual Promethee Software. In the group of seeded grape cultivars, the three top-ranked genotypes were 'Italia Clone I′, 'Dona Maria', and 'Italia Muscat', while in the seedless group, the best-rated were 'BRS Ísis', 'BRS Linda', and 'BRS Morena'. Our research demonstrated, for the first time, the evaluation of grape genotypes using MCDA method with qualitative and quantitative criteria.

Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

This study provides an innovative collaborative spatial decision support system (SDSS) that aims to ensure an equitable spatial distribution of healthcare services. Evaluating the equality of access to health services across different geographical areas is important, as it requires the analysis of various criteria such as the proximity of health centres and hospitals (HCHs), the quality of services offered, connectivity to primary roads, the availability of public transportation hubs, and the density and distribution patterns of HCHs. This purpose is accomplished via the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) methods. The proposed model includes the weights of the criteria, which are determined through the ordered weighted average (OWA) and evaluated based on their ORness, which ranges from 0 to 1. Furthermore, this model is improved by the best–worst fuzzy method (F-BWM). This approach produces a spatial map that clearly shows the equity of healthcare systems in urban environments. The findings show that the maximum score observed in this study was 0.38% (with an ORness value of 1), whilst the minimum score recorded was 0.28%. In the most severe scenario (ORness = 0), over 70% of the region shows different degrees of fairness, ranging from moderate to suitable and very suitable conditions. Governments and health authorities can use this information strategically to allocate resources and address inequities in access to healthcare facilities.

Analytical Hierarchy Process (AHP) and Superdecisions to Select Building Material for Housing Construction at New Capital Nusantara (IKN), East Kalimantan, Indonesia

AHP by Saaty and Super Decisions decided on eight criteria for five alternative building materials in Bew Capital Nusantara. It is designed to facilitate decision-making processes using multi-criteria decision analysis (MCDA) methods. MCDA methods are used when decisions involve multiple criteria or factors. Weighting by these two tools has been able to explain to construction actors that for a housing project location which is 99km from Samarinda to IKN by land, about 1,343 km from Surabaya by land, and 74.6 km from Balikpapan, which can be reached by land. Selection through weighting on both tools, AHP and Super Decision, ensuring that a total of 11,880 housing units with a total budget of IDR 45.2 trillion use materials that meet the requirements for cost, easy-to-work-with, performance, and physical properties.

Using GIS-supported MCDA method for appropriate site selection of parking lots: The case study of the city of Tetovo, North Macedonia

The provision of adequate parking spaces for vehicles has emerged as a prominent and challenging issue confronted by towns, cities, and municipal authorities in recent years. Addressing this problem necessitates a thorough examination of the prevailing physical conditions in existing parking areas, while simultaneously undertaking analyses to identify suitable locations for new parking areas or parking lots. This study focuses on the city of Tetovo, North Macedonia, investigating and assessing the available parking areas while analyzing potential sites in accordance with the city's needs and requirements. To facilitate decision-making, a Multi-Criteria Decision Analysis (MCDA) approach is employed to address the parking site selection analysis problem. The weightage of criteria utilized in the analysis is estimated, and potential parking solutions or site selections for new parking areas are identified through the combined application of Geographical Information System (GIS) and Analytic Hierarchy Process (AHP) techniques, identifying primary and sub-criteria, with a focus on Land Use and Transportation as the main criteria for selecting parking lots. The integration of GIS and AHP offers an effective and optimal methodology for site selection and identifying suitable parking locations. AHP method, applied to criteria, determined relative weights through expert opinions, while GIS facilitated spatial analysis for identifying suitable parking locations. The study identifies accessibility to main roads as the criterion carrying the greatest weight (0.517), while accessibility to cultural facilities holds the lowest weight (0.117). The study serves as a pivotal resource for sustainable urban management and decision-making, providing insights into future urban planning and the identification of suitable parking lot sites to foster sustainable development within the city.

An Alternative Sensitivity Analysis for the Evaluation of MCDA Applications: The Significance of Brand Value in the Comparative Financial Performance Analysis of BIST High-End Companies

Multi-criteria decision analysis (MCDA) applications consist of techniques that enable the decision maker to make clearer decisions in scenarios where there is more than one alternative and criterion. The general approach for sensitivity analysis in MCDA applications implies sensitivity to the weight coefficient. In this study, as an alternative approach, we reinterpret sensitivity by using the statistical relationship between the final ranking produced by an MCDA method and a constant external factor. Thus, we both verify through an anchor and reveal to what extent the change in the weight coefficient changes the external relations of MCDA. The motivation for this study is to propose an alternative sensitivity methodology. On the other hand, brand value is a parameter that contains critical information about the future of the company, which has not integrated into financial performance studies made with MCDAs before. To that end, the financial performance of 31 companies with the highest brand value in Turkey and trading on Borsa Istanbul between 2013 and 2022 was analyzed with seven different MCDA applications via integrating brand value into the criteria for the first time. The study’s findings revealed that the proposed innovative sensitivity tests produced similarly robust results as traditional tests. In addition, brand value has been proved to be an advantageous criterion to be implemented into MCDAs for financial performance problems through the sensitivity analysis made.

Forest fire risk zoning based on fuzzy logic and analytical network process.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

Selection of helicopters for offshore service using three multi-criteria decision analysis methods: AHP-TOPSIS-2N, THOR 2 and Gaussian AHP-TOPSIS-2N

The aviation and oil and gas industries have shown themselves to be quite consolidated in recent years, which corroborates the growing demand for operational excellence from the main players. Therefore, in the face of an increasingly competitive and fierce market, cost reduction is sought in every way, as a competitive differential against competitors. The aircraft fleet composition for offshore services represents a significant logistical cost for companies. Due to that, this paper aims to order 11 aircraft, compared in 13 different selection criteria, by the use of two multi-criteria decision analysis methods: AHP-TOPSIS-2N and THOR 2. In addition, we will propose a new method (Gaussian AHP – TOPSIS-2N) through the association of the Gaussian AHP with the AHP-TOPSIS-2N. The results showed that the aircrafts AW139, H175 and H215 obtained the best performances and the aircrafts S76, H145 and H225 had the worst performances among the alternatives of the study.