Multi-criteria Decision-making Method Research Articles

MCDM Method for Managing the Water Resources Based on Possibility Theory under Bipolar Fuzzy Environment

Background: Uncertainty is a common factor in every real-life decision-making problem. Possibility theory is one uncertainty theory in Fuzzy sets (FS). The possibility-based decision-making under a fuzzy environment is a significant multi-criteria decision-making (MCDM) method. Methods: A bipolar FS is an extension of a fuzzy set. With the bipolarity concept, we can handle both positive and negative thoughts. In this study, we have provided a possibility mean of a bipolar fuzzy number. We have developed a ranking method for bipolar fuzzy numbers using this pos-sibility concept. A novel possibility MCDM method is suggested for solving the water resources management (WRM) in the Nagpur area, Maharashtra State, India. Results: The MCDM technique is an effective tool for solving WRM problems in an area. Many uncertainties and bipolarities occur together in Nagpur water resources. WRM technique with fuzzy is one approach that can be used to solve the area's water problem. We have used the pro-posed MCDM to address the water-related issues of this district. With this proposed MCDM method, numerically, we employed water resource problems under a bipolar fuzzy environ-ment. Conclusion: The Nagpur area is covered by Basaltic rock and faces water shortage. The district is experiencing severe water shortages. Groundwater, surface water, and rainfall are three water resources considered as alternatives. According to the proposed MCDM technique in Nagpur district, Groundwater is the best water source from three flanks: quality of water, affordability, and availability.

A quantum probability theory-based method for heterogeneous multi-criteria group decision making with incomplete probabilistic linguistic preference relations considering the interference effect among decision makers

Quantum probability theory (QPT) reveals that decision makers (DMs) can interfere with each other and thus affect the decision result. However, existing methods of heterogeneous multi-criteria group decision making (HMCGDM) seldom consider the interference effect among DMs. This paper defines an interference degree based on the phase angle difference obtained by QPT to address HMCGDM problems in which the alternative and criteria sets provided by DMs may be different. In addition, the incomplete probabilistic linguistic preference relations (InPLPRs) are introduced to express the evaluation information of DMs. Considering that the same linguistic term may has different meanings for DMs, we construct a consistency-driven optimization model based on the personalized individual semantics (PISs) to estimate the missing information in InPLPR on each criterion provided by DMs and the corresponding complete PLPR (CPLPR). Then, for each DM, the individual weights of criteria and the comprehensive CPLPR on all criteria in the individual criteria set can be obtained by an optimization model. Subsequently, a novel QPT-based model is erected to derive the weights of DMs and the ranking order of alternatives. Finally, an example of tourism evaluation and several sensitivity and comparative analyses are offered to examine the applicability of the proposed method.

Skewness impact through distributional evaluation (SITDE) method: a new method in multi-criteria decision making

In this article, we propose the Skewness Impact Through Distributional Evaluation (SITDE) method for multi-criteria decision-making. Unlike traditional methods ignoring criteria distribution asymmetry, SITDE enhances the decision quality. We use a case-study on electric vehicle selection to illustrate the efficiency of SITDE relative to conventional methods. The comprehensive decision support with SITDE across multiple thresholds is an important aspect of a detailed and balanced decision-making virtue as our results show in case the skewness effects are included. Theoretical backgrounds, typologies practical applications and statistical justifications to confirm the accuracy of SITDE in regarding to limit complexities MCDM scenarios are explained this paper. SITDE enhances a robust decision-making process by accounting for the inherent biases of symmetric assumption models. Moreover, SITDE proves to be extremely useful in cases for dealing with asymmetrical data distributions and skewed datasets humanitarian cause as infected situations are always overwhelming. This broad applicability indicates the potential for wider use with respect to different domains, such as in environmental management and financial risk assessment. Future studies should investigate the adequacy or insufficiency of its fusion with different MCDM methods and explore if this approach would apply a more efficient and valid insight that might enhance decision making in multiple sectors.

Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers

The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry.

ANN-CFD research on key parameters of stirred tank based on multi-objective optimization and decision makers’ preferences

Utilizing the multi-objective optimization (MOO) model and the multi-criteria decision-making (MCDM) method provides solutions for the rarely studied issue of trade-offs between energy consumption and performance in stirred tanks for decision makers across various industrial sectors. MOO optimizes predictions from a data prediction model to generate a Pareto solution set. By examining the influence of subjective weights on dependent variables, target weight proportions for different preferences are established. The MCDM method is then applied to select optimal solutions from the Pareto set for distinct industrial applications. Notably, the optimal solution for preference Np results in an 86.5% reduction in energy consumption, while the solution for preference Nq achieves an ideal state within the Pareto set. Additionally, the optimal solution for preference σ decreases the standard deviation of solids to 9.93% of the baseline value, demonstrating effective energy consumption optimization.

Evaluation of Potential Flood Areas in the Basin of Lake Ladik through AHP and GIS Integration, (Samsun, Türkiye)

Floods are a problem of many countries on a global scale. In Türkiye, especially in the summer months, large floods occur in the Black Sea Region coastal belt. The number and the destructive power of experienced floods are increasing day by day. It is not possible to prevent the occurrence of floods. But it is possible to take the necessary measures to prevent it from turning into a disaster. Recently, susceptibility analyses have been carried out for floods and similar natural disasters and the results help decision-makers. Within the scope of this study, flood susceptibility analysis was carried out by using multiple geographical factors together in the Basin of Lake Ladik of Samsun Province in the Black Sea Region. In the study, Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS) and Remote Sensing (RS) techniques were used, which are multi-criteria decision-making methods. In this context, flood susceptibility analysis of the basin was carried out by using nine (9) different geographical factors (slope, aspect, lithology, soil, basin size, land use, landforms, precipitation, and drainage density). As a result of the study, for floods, there were identified four (4) different levels as low, medium, high, and very high; and 36.77% of the basin was found to be low, 30.03% was medium, 11.43% was high and 21.77% was found to be sensitive to possible floods at a very high level. The results of the study are also important for decision-makers to make flood risk planning.

Techno economic analysis of electrolytic hydrogen production by alkaline and PEM electrolysers using MCDM methods

Hydrogen, a crucial clean and renewable energy source, addresses pressing challenges of energy security and environmental pollution. Water electrolysis for hydrogen production is a promising approach to satisfy the growing demand for sustainable energy. This study uniquely performs a comprehensive techno-economic analysis of hydrogen production using both Alkaline and Proton Exchange Membrane (PEM) electrolyzers, a first in the field to evaluate their performance comprehensively with advanced Multi-Criteria Decision-Making (MCDM) techniques. Leveraging TOPSIS, WASPAS interval methods, and the Best Worst Method (BWM) with fuzzy logic, this research introduces a novel evaluation framework that incorporates a wide-ranging set of factors, including environmental, technical, technological, economic, and social aspects, divided into 30 sub-criteria. These insights offer a comprehensive understanding of each electrolyser's strengths and weaknesses, helping stakeholders make informed decisions about cost reduction in hydrogen production technologies. This has not been done before. Although cost results favour Alkaline electrolysers, PEM electrolysers are attractive for specific applications where their benefits justify the higher initial cost, choosing between Alkaline and PEM electrolysers dependent on a given hydrogen production project's requirements.

New Fermatean Fuzzy Distance Metric and Its Utilization in the Assessment of Security Crises Using the MCDM Technique

The problem of insecurity is a global phenomenon that has several forms like terrorism, banditry, kidnappings, etc. Insecurity has taken hold in the Sub-Saharan Region of West Africa, especially in Nigeria, for over two decades. Nigeria’s security crisis is more pronounced in the Northern Region, with a new wave in the North-Central Region of Nigeria. It is herculean to assess insecurity in the North-Central Region of Nigeria because of the region’s fuzzy or imprecise nature of insecurity. This constitutes the rationale for deploying the Fermatean fuzzy technique to assess insecurity due to the capacity of the Fermatean fuzzy scheme to handle imprecision. To this end, a new Fermatean fuzzy distance metric is presented to evaluate insecurity in the North-Central Region of Nigeria using a multi-criteria decision-making technique. To express the logic for creating the new Fermatean fuzzy distance metric, some existing Fermatean fuzzy distance metrics are discussed, along with their drawbacks. The mathematical properties of the new technique are discussed, and the new method is applied computationally to assess insecurity in the North-Central Region of Nigeria. The data for the security assessment are collected via Fermatean fuzzy linguistic variables using the opinions of security experts and analyzed using the technique for order of preference by similarity to ideal solution, which is a commonly used multi-criteria decision-making method. Finally, the numerical validity of the new technique is expressed with comparative results, and the finding shows the benefit of the new distance approach over the existing methodologies. The outcome of the work will provide reliable traveling advisories for safe voyages within the region.

Electricity security in Uganda: Measurement and policy priorities

Reliable, accessible, affordable, and sustainable electricity systems are fundamental to modern and progressive economies. For developing societies, particularly those with fragile power generation capabilities and electricity networks, the electricity security metrics are incomparable and remain untested. A Multi-Criteria Decision-Making (MCDM) method that follows an entropy-based weighting system is employed to quantitatively evaluate and construct an Electricity Security Index (ESI) for Uganda. Results reveal that Uganda is “moderately” electricity secure. Out of the maximum possible score of 100, a year-on-year analysis indicates that the ESI score was highest in 2007 (56) and the lowest was registered in 2015 (39). Based on the VIKOR technique, it is observed that electricity reliability contributes the most to the ESI, while electricity access contributes the least. Although expansion of electricity generation capacity is necessary, energy policies should, in equal measure, prioritize adequate investments in robust and modern transmission and distribution infrastructure. A riveting policy implication is that governance quality enhances a country's electricity system by reinforcing the other dimensions of electricity security.

Application of a GIS-Based Multi-Criteria Decision-Making Approach to the Siting of Ocean Thermal Energy Conversion Power Plants: A Case Study of the Xisha Sea Area, China

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

AHP VIKOR framework for selecting wind turbine materials with a focus on corrosion and efficiency

The research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution. The research novelty integrates the AHP and VIKOR MCDM methods to address corrosion in wind turbines. By evaluating seven materials against challenging sixteen criteria—including corrosion resistance, mechanical properties, cost, and toxicity, AHP ranks and weights the criteria, while VIKOR identifies the optimal material choice. This dual approach enhances the selection process, ensuring the chosen material improves turbine performance and durability, offering a significant advancement in the sustainable development of wind energy technology. In conclusion, by integrating AHP and VIKOR, it comprehensively evaluates multiple material options based on corrosion resistance, mechanical properties, cost, and environmental impact. This methodology effectively identifies materials that enhance wind turbine performance and extend their lifespan, addressing a critical industry challenge. The alternative exhibits a similarity to the positive ideal solution (Si) of 0.3704 and a relative closeness to the ideal solution (Ri) of 0.0750. Additionally, its priority ranking (Qi) is 0.001, placing it in the first rank for Carbon Fiber Reinforced Polymers (CFRP) within the selection methodology.

Agricultural sustainability assessment in Fars province of Iran through the lens of the elimination multi-criteria decision-making method

The main objective of the present research was to assess agricultural sustainability through the lens of the Elimination Method. Iranian wheat farmers in Fars province comprised the population of the study. Smapling table of Krejcie and Morgan was applied to estimate the statistically plausible sample size. A stratified sampling approach was used for selecting sampling randomly. The research instrument included a structured questionnaire. A panel of experts approved the face and content validities. Average Variance Extracted (AVE), Composite Reliability (CR), and items correlations were used to confirm the convergent validity of the constructs. The average shared squared variance (ASV) and the maximum shared squared variance (MSV) criteria were applied to examine the divergent validity of constructs. Employing the Elimination Method to assess agricultural sustainability in four counties of Fars revealed that Marvdasht is the most sustainable area for the development of wheat cultivation. Because it was able to fulfill 16 indicators out of 23 indicators of agricultural sustainability. The high level of productivity and efficiency of the wheat crop in this region is one of the main reasons for the relatively high sustainability of wheat production practices. Furthermore, the results demonstrated that Darab was the second most suitable region for developing wheat production. Based on the Elimination Method, the region was able to fulfill six indicators out of 23 agricultural sustainability assessment indicators. According to the results of ranking alternatives using the Elimination Method, the two counties of Kazeroun and Eghlid could not acceptably fulfill indicators of agricultural sustainability. In other words, it seems that these two regions are not suitable for the development of wheat production in Fars province. In the end, it was recommended that the Elimination Method can be a useful approach for urgent decision-making and agricultural managers and decision-makers in Fars province should focus more intensively on the development of wheat production in Marvdasht.

Development of the rough Defining Interrelationships Between Ranked criteria II method and its application in the MCDM model

Although numerous methods of multi-criteria decision-making have been developed so far, there are still those that have not been improved by different theories that deal well with uncertainties and inaccuracies that are a normal occurrence in everyday life. The goal of this research is the development of the Rough Defining Interrelationships Between Ranked Criteria II (Rough DIBR II) method and the presentation of its application in the multi-criteria decision-making (MCDM) problem, specifically in human resource management (HRM). The paper presents the subject-developed method and its practical application in the MCDM model with the Rough Additive Ratio Assessment (Rough ARAS) method. In order to check the consistency and validity of the proposed methodology, a sensitivity analysis and a comparative analysis were performed. The conclusions of this research indicate a stable and valid proposed methodology, as well as the possible application of the Rough DIBR II method for defining weighting coefficients of criteria in real-life decision-making problems.

Identification of optimal waste-to-energy strategies for sustainable development in Iran: SWOT analysis, hybrid MCDM methods, and game theory

The growing global focus on environmental sustainability and the pressing need for efficient waste management and energy crisis mitigation have prompted extensive investigations into sustainable waste management strategies. Given Iran's economic development and population growth, the country faces challenges in energy supply and waste management, making waste-to-energy (WtE) applications a promising solution for sustainable waste management. This study employs a combination of SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, Multi-Criteria Decision-Making (MCDM) approaches, and game theory to explore WtE technologies and processes, evaluate their applicability within Iran's context, and identify the most effective WtE strategies for the country. Furthermore, game theory and fuzzy Shapley value analysis were utilized to determine the optimal combination of WtE development strategies. The strategy player “SO” held the highest position of power, with a fuzzy Shapley value of (0.391, 1.744, 3.264), resulting in the identification of the optimal strategy combination of SO2ST2WO1WT2, with a value of (0.429, 0.679, 0.893). The recommended combination emphasizes landfill with gas capture, development of incineration power plants, and integrated resource recovery through residue-derived fuel (RDF) implementation. Achieving these objectives necessitates energy policy reforms, pricing adjustments, improvements in the energy subsidy system, and infrastructure and market development.

The extent of overtourism in some European locations using multi-criteria decision-making methods between 2014 and 2023

Purpose Overtourism has been identified as a significant global problem with numbers of negative externalities. The purpose of this paper is to contribute to the establishment of a standard that objectively measures the extent of tourism to produce a dynamic ranking of selected European settlements, as there is a lack of studies using sophisticated statistical methods to analyse secondary data on overtourism. Design/methodology/approach The 28 selected sites, studied according to their involvement in overtourism, were ranked using multi-criteria decision-Mmaking Methods between 2014 and 2023. Rankings were calculated by VIKOR, TOPSIS and MMOORA, and an aggregate ranking was created by using the cross-entropy optimization. Additionally, the annual changes in the rankings were presented graphically using principal component analysis on a two-dimensional space, referred to as the “sites' space.” Finally, the sites were clustered into three distinct groups based on their level of overtourism: less, medium and more. This was achieved through the use of the K-means algorithm. Findings Following the onset of the pandemic in 2020, there was a notable decline in overtourism. However, following the year 2021, the numbers began to rise once more, and by 2022, they had returned to their pre-pandemic levels. Among the methods, MMOORA demonstrated the most effective performance in comparison to the optimal ranking. Originality/value The applied methods with novel rank aggregation could also shed light on the most relevant indicators to overtourism. These included the number of nights spent in paid accommodation per population, the number of overnight visits per population and the number of air passengers.

The PROMETHEE-GAIA: A multi-criteria decision-making method for identifying best conservation agricultural practices

In a first, we used Preference Ranking Organization Method and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) tool in agricultural research for identifying the best management decision with weakening factors for cultivation of mustard following rice under fifteen regimes of conservation agriculture (CA) practices, because of its versatility, simplicity and usefulness. We created the regime of CA practices based on energy spent for raising the crop combining different tillage practices viz., reduced tillage and zero tillage, and quantity of crop residues and fertilizer application. The performance of the CA regimes was evaluated over the conventional ones using conflicting criteria (31) related to soil, agronomy, plant protection, energy use and economics. With the PROMETHEE-II method, we found zero tillage with 100 % residue plus 75 % NPK (ZERO3) as the best performing alternative, while GAIA analysis identified ZERO3 and zero tillage with 50 % residue plus 100 % NPK (ZERO4). On integration, PROMETHEE-GAIA helped the decision makers to segregate the effects of the criteria on the outcome creating a scope for maneuvering the weak links for optimizing the performance of mustard crop under different CA-regimes. The tool has a huge potential for use in multi-factorial agricultural research.

Selection of Green Recycling Suppliers for Shared Electric Bikes: A Multi-Criteria Group Decision-Making Method Based on the Basic Uncertain Information Generalized Power Weighted Average Operator and Basic Uncertain Information-Based Best–Middle–Worst TOPSIS Model

This study introduces a novel multi-criteria group evaluation approach grounded in the theory of basic uncertain information (BUI) to facilitate the selection of green recycling suppliers for shared electric bikes. Firstly, a comprehensive index system of green recycling suppliers is established, encompassing recycling capacity, environmental sustainability, financial strength, maintenance capabilities, and policy support, to provide a solid foundation for the scientific selection process. Secondly, the basic uncertain information generalized power weighted average (BUIGPWA) operator is proposed to aggregate group evaluation information with BUI pairs, and some related properties are investigated. Furthermore, the basic uncertain information-based best–middle–worst TOPSIS (BUI-BMW-TOPSIS) model incorporating the best, middle, and worst reference points to enhance decision-making accuracy is proposed. Ultimately, by integrating the BUIGPWA operator for group information aggregation with the BUI-BMW-TOPSIS model to handle multi-criteria decision information, a novel multi-criteria group decision-making (MCGDM) method is constructed to evaluate green recycling suppliers for shared electric bikes. Case analyses and comparative analyses demonstrate that compared with the BUIWA operator, the BUIGPWA operator yields more reliable results because of its consideration of the degree of support among decision-makers. Furthermore, in contrast to the traditional TOPSIS method, the BUI-BMW-TOPSIS model incorporates the credibility of information provided by decision-makers, leading to more trustworthy outcomes. Notably, variations in attribute weights significantly impact the decision-making results. In summary, our methods excel in handling uncertain information and complex multi-criteria group decisions, boosting scientific rigor and reliability, and supporting optimization and sustainability of shared electric bike green recycling suppliers.

Review of The Financial Health of Bank During Increasing Foreclosed Assets and The Application of Analytic Hierarchy Process (AHP) in Selecting Strategies to Reduce Them

PT Bank Laju International Tbk (the Bank) has struggled with its increased foreclosed assets, particularly those originating from mortgage loans, which could affect its financial health. The research assessed Bank’s financial health using Risk Based Bank Rating (RBBR) framework by analysing key financial ratios and investigating the root causes of rising foreclosed assets through Fishbone and Pareto analysis. Key factors include customer income instability, slow progress in selling foreclosed assets, and lack of insurance protection during economic downturns. To select effective strategies for managing foreclosed assets, the research utilized Analytic Hierarchy Process (AHP), a Multi-Criteria Decision-Making method, to evaluate multiple alternatives based on various criteria, which were derived from Focus Group Discussion (FGD) with Bank’s officers, who directly involved in mortgage loans and foreclosed assets activities, also reference with Bank’s SWOT analysis. The research evaluated three alternatives strategy: Protection Insurance for Customer’s Mortgage Loans. Actively Partnering with property agents to accelerate sale of foreclosed assets as-is. Collaborating with property agents to renovate foreclosed assets. The result showed that despite the increase in foreclosed assets, the Bank remains financially sound, with key financial ratios within acceptable regulatory limits. AHP analysis revealed that alternative 1 stands in first place to be prioritized, followed by alternative 2, however between both alternatives indicates a very small difference in prioritization weight, which means that both strategies are important to be executed and prioritized. Proposal to implement both alternatives in parallel would be a very effective strategy, where alternative 1 conduct as Preventive Strategy in preventing customer’s mortgage loans defaults, while alternative 2 as Corrective Strategy in lowering foreclosed assets volume. Alternative 3 acts as a complement strategy, where renovating foreclosed assets could facilitate quicker sales, however it’ll take longer time for renovation itself.

A cognitive load assessment method for fighter cockpit human-machine interface based on integrated multi-criteria decision making

The primary interface for communication between pilots and aircraft systems is the fighter cockpit Human-Machine Interface (HMI). Since reduced cognitive load ensures that pilots will operate the aircraft safely and effectively, it is critical to evaluate pilot cognitive load during HMI. A cognitive load assessment method, based on multi-criteria decision-making, is proposed to accurately quantify the relationship between the HMI and the cognitive load in the fighter’s cockpit. Firstly, based on the integrated Multi-Criteria Decision-Making (MCDM) method, the Step-wise Weight Assessment Ratio Analysis (SWARA) and MEthod based on the Removal Effects of Criteria (MEREC) methods are used to assign subjective and objective weights, respectively. Moreover, the Combined Compromise Solution (CoCoSo) method is applied to rank the scenarios to establish a cognitive load assessment model for the cockpit HMI of the fighter jet. Secondly, an evaluation standard system of fighter cockpit HMI is proposed, drawn upon multiple sets of eye-movement criteria and subjective assessment criteria. Moreover, cognitive load experiments of fighter cockpit HMI are conducted using eye-tracking technology to get the objective physiological cognitive data as well as the subjective assessment data of the subjects. Consequently, the parameter data sets of the eye-movement criteria and the subjective criteria for the evaluation of cognitive load are obtained. The proposed method is applied to analyze the cognitive load assessment of a fighter jet cockpit HMI layout. This application aims to verify the effectiveness of the assessment method in evaluating the cognitive load of the HMI layout. Through sensitivity and comparison analyses, the model was further verified to have excellent robustness and applicability for cognitive load assessment. The advantages of this method can be seen through the comparison, which is that it has higher discriminability when assessing the degree of cognitive load. At the same time, it has higher flexibility in dealing with complex and ambiguous cognitive load assessment information.

An updated multi-criteria decision-making method for the sustainable renovation of buildings including environmental, economic and social life-cycle metrics

The ambitious targets of carbon emission reduction set worldwide for the coming years entail the commitment of structural engineers towards the sustainable renovation of existing buildings. The life cycle thinking (LCT) approach offers a holistic perspective for the design of sustainable retrofitting strategies. It envisages the reduction of the environmental impact at all building life cycle phases, while also addressing economic and social issues. Multi-criteria decision-making (MCDM) approaches support the choice of optimal retrofitting solutions, thus being relevant tools for boosting the actual adoption of LCT in current practices. In this study, a previously proposed MCDM approach is enriched with additional LCT-inspired decision parameters (module D beyond-life impacts, environmental payback period, invasiveness), and is then scrutinised and discussed through its application to a case-study building. Four integrated retrofitting scenarios are investigated using state-of-art seismic loss and energy performance assessment methods, including four different types of exoskeletons, made of timber, steel, and concrete. The end-to-end integrated assessment shows that the inclusion of additional LCT-inspired decision criteria effectively favours LCT-based retrofitting interventions over more traditional ones.