Multi-criteria Analysis Method Research Articles

Application of a multi-criteria decision support system for assessing development potential in flood risk areas - Case study of the Warta River

The paper discusses the concept of a proprietary decision-making model that allows for determining whether the planned development in areas not protected by flood embankments and at risk of flooding can be shaped in a safe manner. The model was used to evaluate the possibility of shaping the development in flood-risk areas on the example of one of the types of Olęder villages – a dispersed village located in the floodplains of the Warta River (western Poland). So far, there has been no comprehensive evaluation method supporting proper spatial planning for flood-risk areas. The use of multi-criteria analysis methods enabled to specify the key criteria of this evaluation, which form the basis of the decision-making support system. Additionally, the elaborated method enables to determine whether the localities under study can retain their current functional nature and if there is a potential for further spatial development based on the characteristics of an Olęder village. The presented methodology can be easily adapted to other cultural areas located in countries with different levels of development, traditions, landscape or climate.

Economic and Technical Assessment of the Chinese Plum Varieties Using Multi-Criteria Analysis Methods

Economic and Technical Assessment of the Chinese Plum Varieties Using Multi-Criteria Analysis Methods

A Fuzzy Entropy Approach for Portfolio Selection

Portfolio management typically aims to achieve better returns per unit of risk by building efficient portfolios. The Markowitz framework is the classic approach used when decision-makers know the expected returns and covariance matrix of assets. However, the theory does not always apply when the time horizon of investments is short; the realized return and covariance of different assets are usually far from the expected values, and considering additional factors, such as diversification and information ambiguity, can lead to better portfolios. This study proposes models for constructing efficient portfolios using fuzzy parameters like entropy, return, variance, and entropy membership functions in multi-criteria optimization models. Our approach leverages aspects related to multi-criteria optimization and Shannon entropy to deal with diversification, and fuzzy and fuzzy entropy variants provide a better representation of the ambiguity of the information according to the investors’ deadline. We compare 418 optimal portfolios for different objectives (return, variance, and entropy), using data from 2003 to 2023 of indexes from the USA, EU, China, and Japan. We use the Sharpe index as a decision variable, in addition to the multi-criteria decision analysis method TOPSIS. Our models provided high-efficiency portfolios, particularly those considering fuzzy entropy membership functions for return and variance.

Penerapan Sistem Pendukung Keputusan Untuk Seleksi Mahasiswa Berprestasi Menggunakan Metode Copras

Technological developments are increasingly rapid, students must be able to adapt to changes, be enthusiastic about learning, and care about sustainable development. Therefore, the Independent Campus Learning Policy (MBKM). A Decision Support System (DSS) or Decision Support System (DSS) is a system that is able to provide problem solving capabilities and communication capabilities for problems with semi-structured and unstructured conditions. The COPRAS method or Combination of Ratio Assessment is a multi-criteria decision analysis method used the alternatives involved in a decision. This research aims to obtain ranking results of outstanding students quickly and objectively without requiring a lot of effort. The results of this ranking will help Graha Nusantara Padangsidimpuan University, especially the Faculty of Engineering, Computer Science Study Program, in selecting outstanding students. From the conclusion above, the student selected to be in first place is A3 in the name of Benny Matondang with a score of 99.972 in first place.

Multi-Criteria Decision Analysis (MCDA) for sustainability assessment in food sector. A systematic literature review on methods, indicators and tools

Multi-Criteria Decision Analysis (MCDA) for sustainability assessment in food sector. A systematic literature review on methods, indicators and tools

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.

Development of a decision support tool to compare diagnostic strategies for establishing the herd status for infectious diseases: An example with Salmonella Dublin infection in dairies

The diagnosis of infectious diseases at herd level can be challenging as different stakeholders can have conflicting priorities. The current study proposes a “proof of concept” of an approach that considers a reasonable number of criteria to rank plausible diagnostic strategies using multi-criteria decision analysis (MCDA) methods. The example of Salmonella Dublin diagnostic in Québec dairy herds is presented according to two epidemiological contexts: (i) in herds with no history of S. Dublin infection and absence of clinical signs, (ii) in herds with a previous history of infection, but absence of clinical signs at the moment of testing. Multiple multiparty exchanges were conducted to determine: 1) stakeholders’ groups; 2) the decision problem; 3) solutions to the problem (options) or diagnostic strategies to be ordered; 4) criteria and indicators; 5) criteria weights; 6) the construction of a performance matrix for each option; 7) the multi-criteria analyses using the visual preference ranking organization method for enrichment of evaluations approach; 8) the sensitivity analyses, and 9) the final decision. A total of nine people from four Québec’s organizations (the dairy producers provincial association along with the DHI company, the ministry of agriculture, the association of veterinary practitioners, and experts in epidemiology) composed the MCDA team. The decision problem was “What is the optimal diagnostic strategy for establishing the status of a dairy herd for S. Dublin infection when there are no clinical signs of infection?”. Fourteen diagnostic strategies composed of the three following parameters were considered: 1) biological samples (bulk tank milk or blood from 10 heifers aged over three months); 2) sampling frequencies (one to three samples collection visits); 3) case definitions to conclude to a positive status using imperfect milk- or blood-ELISA tests. The top-ranking diagnostic strategy was the same in the two contexts: testing the bulk tank milk and the blood samples, all samples collected during one visit and the herd being assigned a S. Dublin positive status if one sample is ELISA-positive. The final decision favored the top-ranking option for both contexts. This MCDA approach and its application to S. Dublin infection in dairy herds allowed a consensual, rational, and transparent ranking of feasible diagnostic strategies while taking into account the diagnostic tests accuracy, socio-economic, logistic, and perception considerations of the key actors in the dairy industry. This promising tool can be applied to other infectious diseases that lack a well-established diagnostic procedure to define a herd status.

Integrating fuzzy analytic hierarchy process into ecosystem service-based spatial planning: A case study of the Shenyang metropolitan area, China

Incorporating ecosystem services (ESs) into spatial planning is crucial for effective environmental management and achieving sustainable development goals. While the Analytic Hierarchy Process (AHP) is a commonly employed method for multicriteria analysis of ESs, it has faced criticism for its limited ability to handle inherent imprecision and uncertainties. Consequently, we proposed an assessment framework for ESs using the Fuzzy Analytic Hierarchy Process (FAHP) and implemented it in the Shenyang Metropolitan Area (SMA), a key political and economic center in Northeast China. We quantified eight types of ESs (water yield, food supply, water regulation, carbon storage, waste regulation, soil retention, habitat quality, and outdoor recreation) within SMA. The FAHP was utilized to determine the weights of these ESs. Subsequently, we presented a normalized index to identify priority conservation and development areas. Our results indicated that the primary areas for conservation were mainly located in the southwest and east of Benxi City, the southeast of Fushun City, and the southeast of Anshan City, whereas areas for development were primarily in the northwest of Shenyang City. Through comparing various ES integration methods, our study underscores the effectiveness of FAHP in ES evaluation. The research also highlights the challenge of managing uncertainties in ES-based policy-making and emphasizes the necessity for resilient and comprehensive planning approaches.

Evaluation of the Budget Management of Local Government Units in Poland Based on Methods of Multi-Criteria Analysis in 2019-2021

The idea of the present paper was to assess budget management in local government units in Poland in 2019-2021 using multi-criteria analysis methods. The evaluation was broken down by different types of LGUs using the TOPSIS method based on min-max normalization. The survey was conducted using secondary data obtained from the Ministry of Finance website, broken down by budget (per capita) and debt indicators. For all LGUs in total, the best position in 2019-2021 was found in voivodeships, whose ranking remained unchanged despite the COVID-19 pandemic. An analogous situation was observed in rural municipalities. The last position in the ranking was occupied by towns with powiat status (2019) and metropolitan areas (2020-2021). Between 2019 and 2021, the number of entities placed in financial condition class 2 was increasing only in towns with powiat status. A reduction in financial condition (in Class 2) was also evident in rural municipalities, in powiats, and metropolitan areas. Over the years 2019-2021, there was a reduction in the number of entities with financial condition class 3 in rural municipalities and towns with powiat status. The leaders in benchmarking in rural communes were Kleszczów and Godkowo; urban-rural communes: Kamieńśk and Lubniewice; urban communes: Krynica Morska and Hel; cities with county rights: Sopot and Świnoujście, metropolises: Katowice and Warsaw, voivodeships: Pomeranian and Greater Poland. The powiats were characterized by great diversity, the best places in the ranking in individual years went to the Wolsztyński, Sztumski and Golubsko-Dobrzański powiats.

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.

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.

Possibility to use decision-making methods for project management information system

Project management in today's world is an important task that requires constant decision-making to successfully complete projects. Project Management Information Systems (IMS) help with this, but their ability to use decision-making methods is often limited and the decision-making process itself is the responsibility of the project manager or other stakeholders. However, the use of decision-making techniques can significantly improve the efficiency and effectiveness of project management by considering various factors and alternatives. In the course of the study, an analysis of decision-making methods, such as the method of decision-making based on data, the method of optimization, the method of selecting scenarios, the method of prioritization, the method of balancing resources, the method of multi-criteria analysis, was carried out for the possibility of integration into the modules of the IMS to improve project management. The classification of project management information systems based on modules is also presented and described and a description of these modules is provided. As a result, it is found that the method of selecting scenarios, the method of prioritization and the method of multi-criteria analysis can be effectively used in separate, defined, modules for decision-making in the project environment. Integrating these methods into the IMS can help project managers make better decisions that meet the needs and goals of the project. This study confirms the importance of using decision-making techniques in IMS to improve project management. The integration of these methods will reduce risks, optimize costs and increase management efficiency. These findings stimulate further development of the functionality of the IMS and contribute to further research in this area.

Landslide Susceptibility Assessment in Nuwakot: An Examination of Methods to Mapping

The highest re-occurring hazard incident in Nepal in 2022 is reported to be fi re and landslides. A comprehensive study on understanding and identifying landslide susceptible areas and planning accordingly is perhaps one approach to disaster preparedness. In this context, landslide susceptibility assessment (LSA), plays a key role as a preparedness and mitigation tool at the local level. Landslide susceptibility, theoretically, denotes a geographic location of potential reoccurrence of landslide in an area based on several causative factors. I have conducted this study to explore landslide occurrence in Nepal based on secondary data, and map landslide susceptibility in Nuwakot district by using spatial multi-criteria analysis, SMCA and frequency ratio (FR) method. Then, I have evaluated the results which will support preliminary landslide risk level identification at the local level. Existing secondary data and landslide inventory extracted using satellite imageries were major data sources. Landslides in Nuwakot are concentrated within the range of 1000-1500-meter elevation of 15-25-degree convex slope with gneisses/schists formation. A result using SCMA methodology shows 47% area of Nuwakot under landslide susceptibility, of which 13.6% is highly susceptible whereas FR method resulted 27% area under high susceptible zone. The variation in susceptibility level and area between SCMA and FR methods can be attributed to differential calculated weight factor to geological factors, such as fault, lineament, and lithology. This study concludes that irrespective of methods adopted, landslide susceptibility maps and output data provide useful tools for landslide hazard risk identification and management. The necessity of robust and commonly applicable guidelines at different geographic scales is also obvious.

District heating system's development decarbonization strategy assessment by system dynamics modeling and multi-criteria analysis

The study introduces a hybrid model that integrates system dynamics modeling and multi-criteria analysis. Through the system dynamics model, the study examines energy, economic, and environmental indicators of a District Heating (DH) company, assessing its dynamics until 2050. Various decarbonization scenarios are explored, involving the transition of the DH system to a 4th generation DH (4GDH) system based on four strategies: utilizing at least (a) 50% Renewable Energy Sources (RES), (b) 50% waste heat, (c) 75% cogenerated heat, or (d) 50% of the combined aforementioned energy and heat. Additionally, development scenarios incorporate measures to enhance energy efficiency on the consumer side and within the heating networks. The sustainability of each scenario is evaluated using the multi-criteria analysis method TOPSIS. The hybrid model establishes a ranking of the transition pathways based on their sustainability scores and benchmarks the results of the developed scenarios against a carbon-neutral DH system. This model serves as a valuable guide for DH system developers and decision-makers. The study focuses on Riga as a practical case study.

Allocation of reservoirs sites for runoff management towards sustainable water resources: Case study of Harirud River Basin, Afghanistan

The intensification of drought conditions in arid and semi-arid regions coupled with the growing population increased water demands (domestic, and irrigation). It signifies the importance of addressing the pressing need for sustainable water resource management. Seventeen criteria spanning topographical, hydrological, geological, environmental, and socio-economic categories, were used for dam site suitability analysis for Harirud River Basin, Afghanistan. Weighted Linear Combination (WLC) model and Geographic Information System (GIS) were employed to perform multi-criteria analysis (MCA) method. The results revealed that the final suitability map exposed 12.31 % highly suitable, 21.0 % moderately suitable, and 66.68 % non-suitable sites, totaling 125.8 km, 214.6 km, and 681.4 km, respectively. Segmentation accuracy assessment was utilized to evaluate the existing dam’s accuracies. The study revealed that accuracies of 84.65 % for the Salma Dam and 88.08 % for the Pashdan Dam were achieved, respectively. Six new dams, along with the existing two, formed the series of eight dams. The dam series were optimized for the total annual runoff of (1,600,000,000 m3), and the final dam heights were determined as follows: 107.5 m, 42 m, 100 m, 23.9 m, 30 m, 18 m, 23.44 m, and 22.65 m for dams (1 to 8), respectively. The study underscores the methodology's superiority in site suitability analysis and runoff optimization, while recommending future focus on observational data and higher-resolution digital elevation model (DEM) files for enhanced precision, environmental impact assessment, climate change considerations, social and economic implications, improved data resolution, and transboundary cooperation.

Sustainability of European agri-food supply chain using MRP-PCI multicriteria analysis method

The need for a more sustainable agri-food system is a topic that has attracted growing interest in recent years. Several international and European policies such as Agenda 2030 and the European Green Deal have been defined with the aim of making agri-food systems more sustainable at all stages of the supply chain, from production to consumption. Particularly, the European Union concentrates several policies on it. Therefore, the assessment of the level of sustainability among the states of the European Union is a key aspect to properly address and evaluate the implementation of these policies. The objective of this paper is to measure the sustainability of the global agri-food supply chain (AFSC) of the European Union countries through the application of a multi-criteria analysis. In particular, the method used is the Multiple Reference Point Partially Compensatory Indicator, which allows the creation of composite indicators using different levels of compensation across them. A set of 50 indicators, referred to 2011 and 2019, were built and then divided into the three basic dimensions of sustainability (economic, social and environmental), aggregated into the four main AFSC sectors (agriculture, food industry, distribution, and consumption) in order to obtain an overall sustainability index. Through such an index we provided a sustainability ranking for the EU countries, while the analysis of dimensions of each sector contributed to increase the knowledge about the supply chain that can be used by decision-makers. According to the results, Italy achieved the best level of sustainability of the AFSC with a value of 48.53, followed by Sweden, Austria, Spain, France, Germany, the Czech Republic, Portugal and Slovakia. In relation to the different sectors, the biggest problems were observed in the consumption sector, where most countries did not perform well, especially for the social dimension (e.g. excess of overweight and obese persons). In contrast, the performance of the agricultural sector was good, with few exceptions, showing a fair state of sustainability.

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.