Search Results (80)

Assessing the urban green transportation development level (UGTDL) is of great significance for addressing traffic issues in megacities and promoting urban sustainable development. An evaluation framework for the UGTDL is proposed based on Multi-Criteria Decision Analysis (MCDA) methods. Firstly, from both macro and micro perspectives, a comprehensive evaluation indicator system is constructed, covering multiple dimensions such as traffic spatial organization efficiency, green travel, new energy vehicle development, traffic safety, and the traffic environment. Secondly, to address the uncertainties and fuzziness in the evaluation process, the Probability Language Term Set (PLTS) is introduced to represent expert evaluation information, thereby reducing the information loss. Thirdly, the improved Step-wise Weight Assessment Ratio Analysis (SWARA) method is employed to calculate the weights of the indicators, improving the computational efficiency. Finally, the extended Combined Compromise Solution (CoCoSo) method is used to calculate the UGTDL, avoiding the compensatory issues in the traditional decision-making methods. The proposed approach is applied to assess the UGTDL in Guangzhou from 2020 to 2023. The results show that the UGTDL scores for Guangzhou from 2020 to 2023 are 1.6367, 2.2325, 2.1141, and 1.8575, respectively. Sensitivity analysis verifies the effectiveness and stability of the approach. Further obstacle analysis shows that the promotion of new energy vehicles (NEVs) has led to a marginal decrease in the utility of Guangzhou’s UGTDL. In the future, Guangzhou should take further measures to improve the traffic space organization efficiency and traffic safety. Full article

Background/Objectives: The COVID-19 pandemic underscored the need for adaptive public health strategies and effective decision-making tools to optimize clinical responses and policy measures based on regional contexts. This study aims to identify key criteria for developing a patient-centered strategy to enhance the resilience of Romania’s healthcare system during the pandemic. Methods: This research introduces a Multi-Criteria Decision Analysis (MCDA) model using the Simple Multiple Attribute Assessment Technique (SMART) to integrate quantitative and qualitative data, providing decision-makers with a structured tool for improving healthcare resilience. A survey of 412 Romanian healthcare professionals identified critical risks and opportunities. The study followed a two-phase approach: first, analyzing expert perceptions to determine key challenges; second, applying a mixed-methods evaluation to prioritize resilience-building strategies. Results: Four main challenges emerged: (1) healthcare workforce shortages causing excessive workload and stress, (2) poor communication and systemic inefficiencies limiting patient access, (3) weak crisis management due to delayed control measures, and (4) regulatory gaps leading to fragmented responses. Proposed solutions included workforce training, improved communication, telemedicine integration, increased financial support, and a unified legal framework. The SMART method facilitated the structured prioritization of these measures, with long-term system sustainability emerging as the most effective strategy for preventing future crises. Conclusions: This study demonstrates the value of integrating MCDA into healthcare decision-making, offering a scalable model for policymakers to enhance crisis response and resource allocation. By incorporating expert insights and patient needs, the proposed framework strengthens healthcare system preparedness, contributing to informed, patient-centered decision-making and long-term resilience. Ultimately, our findings not only contribute to the existing literature but may also open new directions to facilitate informed, patient-centered decision making, thereby strengthening the resilience of healthcare systems in crisis situations. Full article

The operational condition of fire water supply aims to ensure the continuous and reliable supply of high-pressure water in emergency situations. Assuming a fire breaks out in a mountain village located far from the city center, due to the significantly higher flow rate and velocity of the water supply pipeline compared to normal operating conditions, any malfunction or shutdown of the pump caused by improper operation could result in catastrophic damage to the pipeline system. In response to the call for sustainable development, addressing this urgent academic challenge means finding a way to safely and economically maintain a continuous water supply to the target water demand point, even under extreme accident conditions. In this paper, drawing on engineering examples, we considered air tanks with varying process parameters installed at multiple locations within a water conveyance system to prevent water hammer and ensure water supply safety. To ensure that air tanks are of high quality and cost-effective after procurement and use, a multi-objective optimization design model comprising fitting, optimization, and evaluation plates was constructed, aimed at selecting certain process parameters. In the multi-objective optimization design model, Latin hypercube sampling improved by simulated annealing (LHS-SA), stepwise regression analysis (SRA), the Multi-Objective Whale Optimization Algorithm (MOWOA), and the Multi-Criteria Decision Analysis (MCDA) method with various weight biases are used to ensure the rationality of the optimization process. By comparing the optimization results obtained using these different MCDA methods, it is evident that the results output after AHP-EWM evaluation tend to be economic indicators, whereas the results output after FN-MABAC evaluation tend to be safety indicators. In addition, according to the sensitivity analysis of weight distribution, it can be inferred that the changes in maximum transient pressure head caused by water hammer have the most significant impact on final decision-making. Full article

The automotive industry is responsible for about 20% of greenhouse gas emissions in Europe, and it is under notable pressure to meet the reduction targets set by the European Union for the next decades. In this context, lightweighting is a very effective design strategy for which materials selection plays a key role. One of the main challenges of lightweighting is selecting materials with enhanced structural properties but a reduced weight in comparison with traditional solutions. The spectrum of available materials is very large, and the choice needs to be carefully evaluated based on multiple factors, such as mechanical behavior, raw materials cost, the availability of manufacturing processes, and environmental impact. This article presents an innovative methodology for materials selection in the lightweight automotive field based on the Ashby approach for mechanical performance coefficients as an initial filtering criterion. Following this preliminary screening, this study adopts the VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) MCDA (Multi-Criteria Decision Analysis) technique to rank feasible design solutions based on case study boundary conditions. The evaluation criterion of different design options encompasses crucial factors, such as mechanical properties, cost considerations, and environmental impact measures. The method is finally validated by the application of a redesign case study, a motor bracket of an electric commercial car. Full article

Drug discovery is inherently a multi-criteria optimization problem. In the first instance, it involves a tremendously large chemical space, where each compound can be characterized by multiple molecular and biological properties. Modern computational approaches try to efficiently explore the chemical space in search of molecules with the desired combination of properties. For example, Pareto optimizers identify a so-called “Pareto front”, a set of non-dominated solutions. From a qualitative perspective, all solutions on the front are potentially equally desirable, each expressing a trade-off between the goals. However, often there is a need to weight the objectives differently, depending on their perceived importance. To address this, we recently implemented a new Multi-Criteria Decision Analysis (MCDA) method as part of the AI-powered Drug Design (AIDD^TM) technology initiative. This allows the user to weight various objective functions differently, which, in turn, efficiently directs the generative chemistry process toward the desired areas in chemical space. Full article

Environmental decision making is a complex process that requires the consideration of multiple factors. Therefore, Multiple-Criteria Decision Aiding (MCDA) aims to address the challenges of environmental decision making. This paper analyses published review papers that discuss the use of MCDA in environmental problems, with the goal of drawing useful meta-level conclusions. The review papers were categorised by application field and sorted by various criteria. The main findings of each paper were also analysed. The analysis reveals that MCDA publications in the specific domain have shown a strong upward trend. Hybrid MCDA is increasingly being applied as it can cope with the multidimensional challenges of environmental decision making. AHP appears to be the most widespread method. The sustainable energy sector is particularly interested in the use of MCDA. However, while decision-makers extensively use MCDA in environmental problems, its corresponding application in real-world settings is not always satisfactory. Full article

This study analyzed the operational environment of supply chains involved in the production of eco-friendly plastics, with a particular emphasis on small- and medium-sized businesses worldwide. Qualitative research methods were used to highlight the significance of extended producer responsibility (EPR) regulations and strong recycling programs for the sustainability of small- and medium-sized enterprises (SMEs). Also, this study looked at international regulations affecting the implementation of circular economy strategies and the difficulties in creating sustainable supply chains. It concluded that waste reduction, effective supply chain management, and sustainable practices are crucial aspects of a more effective and sustainable global plastic-manufacturing sector. This research highlighted the significance of government policies in SME revival and used Multiple-Criteria Decision Analysis (MCDA) to help SMEs adopt sustainable supply chain practices that act as a catalyst for industry reform. Full article

Urban energy systems planning presents significant challenges, requiring the integration of multiple objectives such as economic feasibility, technical reliability, and environmental sustainability. Although previous studies have focused on optimizing renewable energy systems, many lack comprehensive decision frameworks that address the complex trade-offs between these objectives in urban settings. Addressing these challenges, this study introduces a novel Multi-Criteria Decision Analysis (MCDA) framework tailored for the evaluation and prioritization of energy scenarios in urban contexts, with a specific application to the city of Bozen-Bolzano. The proposed framework integrates various performance indicators to provide a comprehensive assessment tool, enabling urban planners to make informed decisions that balance different strategic priorities. At the core of this framework is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is employed to systematically rank energy scenarios based on their proximity to an ideal solution. This method allows for a clear, quantifiable comparison of diverse energy strategies, facilitating the identification of scenarios that best align with the city’s overall objectives. The flexibility of the MCDA framework, particularly through the adjustable criteria weights in TOPSIS, allows it to accommodate the shifting priorities of urban planners, whether they emphasize economic, environmental, or technical outcomes. The study’s findings underscore the importance of a holistic approach to energy planning, where trade-offs are inevitable but can be managed effectively through a structured decision-making process. Finally, the study addresses key gaps in the literature by providing a flexible and adaptable tool that can be replicated in different urban contexts to support the transition toward 100% renewable energy systems. Full article

This paper presents a summary and review of life cycle sustainability assessment (LCSA) methods for the transport sector. The paper provides a comprehensive overview of articles that employ a variety of methods for assessing sustainable development in the transport sector, taking into account the economic, social, and environmental dimensions. In the sustainability assessment of transport, three methods were evaluated: life cycle assessment (LCA), life cycle cost analysis (LCC), and social life cycle assessment (SLCA). An overview of sustainability assessment methods in transport and a review of the indicators used in the life cycle sustainability assessment was conducted. It was found that the selection of indicators within the LCSA for assessing various aspects of sustainable development is dependent on various geographic and policy contexts. An overview of the application of multi-criteria decision analysis (MCDA) methods to assess LCSA in the transport sector was performed. MCDA methods are used to support decision-making regarding the selection of the most sustainable transport options and allow for the simultaneous consideration of multiple criteria, enabling a more sustainable assessment of different transport options. MCDA methods help to rank alternative transportation fuels and help decision-makers consider indicators encompassing economic, environmental and social aspects. Full article

The aim of this paper is to present a decision support system (DSS) to capture the complexity of the transition of a national energy system to net zero in the context of multiple sustainability themes. The paper proposes an integrated assessment framework that combines dynamic systems modeling, sustainability indicators, and multi-criteria decision analysis (MCDA) with direct stakeholder involvement. To illustrate the use of the DSS, the paper compares bundles of climate change policies that aim to decarbonize the road transport sector in Iceland. Eighteen scenarios and alternative development trajectories are defined for the Icelandic energy system based on a combination of three main driving forces. These are, firstly, economic development (three cases); secondly, changes in energy efficiency (two cases); and finally, three climate policy bundles aimed at increasing the share of electric vehicles. Based on the results from the integrated assessment framework, the performance scores of the climate policy bundles are compared across the following five sustainability themes: social impact; economic development; environmental impact; energy security; and technical aspects. The findings confirm that a different conclusion may be reached when multiple sustainability themes are applied in the selection of preferred policy bundles as compared to conventional techno-economic criteria. Banning the registration of fossil-fueled vehicles, combined with economic instruments, offers the best decarbonizing strategy to reach climate and energy policy goals simultaneously. Full article

The development of sponge cities advocates for sustainable urban rainwater management, effectively alleviating urban flood disasters, reducing non-point-source pollution, and promoting the recycling of rainwater resources. Low-Impact Development (LID) serves as a key strategy in this context, providing essential support for urban rainwater control and pollution reduction. To investigate the runoff control effects of LID measures and to reveal the relationship between facility runoff control performance and installation scale, this study focuses on a sponge community in Beijing. A SWMM model was constructed to analyze the rainwater flood control and pollutant load reduction effects of different LID facilities, including bio-retention cells, green roofs, and permeable pavements. Using evaluation indicators such as surface runoff, node overflow, and pollutant control rates, this study examined how facility performance varies with installation scale under different rainfall conditions. The combination scheme of LID equipment optimal configuration is designed by using multiple criteria decision analysis (MCDA) and cost–benefit theory. The results indicate significant differences in performance among the various LID facilities across different rainfall scenarios. Specifically, the optimal installation proportion for runoff and overflow control of permeable pavements were found to be between 30% and 70%. Green roofs demonstrate superior performance in handling extreme rainfall events, while bio-retention cells exhibit significant effectiveness in controlling Total Suspended Solids (TSSs). Through comprehensive performance evaluation, this study identified the optimal combination scale under a 3-year rainfall recurrence interval as 30% permeable pavements, 20% green roof, and 60% bio-retention cells. This combination effectively leverages the strengths of each facility, ensuring system stability and efficiency while also demonstrating optimal management efficiency in cost–benefit analyses. The findings of this research provide valuable insights for future urban water management and infrastructure development. Full article

Green hydrogen can be generated through electrolysis using electricity from renewable sources, such as wind and solar, to split water into hydrogen. This study evaluates the green hydrogen supply chain (GHSC) upstream process using the two-phase integrated multi-criteria decision analysis (MCDA) framework. In the first phase, the data envelopment analysis (DEA) technique is applied to measure the relative efficiency of provincial alternatives with multiple criteria. The input criteria include provincial area, population density, gross domestic product value, and land cost data. In contrast, the sustainability-based governmental criteria concerning people, prosperity, planet, peace, and partnership indices are used as output criteria. Then, the technique for order of preference by similarity to ideal Solution (TOPSIS) is further applied to evaluate regional districts for Ubonratchathani province, one of the twelve relatively efficient provinces, to obtain the ranking list of potential renewable energy sites in the GHSC. Criteria related to geographic and climate data relevant to the efficiency of solar and wind are, thus, collected and analyzed. Our results show that the top three district areas are Kut Khaopun District, Pho Sai District, and Na Tan District, respectively. Finally, the obtained results are verified to evaluate the robustness of the assessment. Our results offer a strategic and practical analysis for policymakers involved in the energy site appraisal process. Full article

Land use/cover change(LUCC) has a significant impact on the ecological environment. Within the Belt and Road Initiative (BRI), as the largest cross-spatial cooperation initiative in human history, one of the core issues is how to scientifically and effectively use and manage the land in the region to prevent the destruction of important ecological and environmental resources. In order to reduce impact on the latter, in this study, we used the bivariate choropleth–multiple-criteria decision analysis (BC-MCDA) method based on the connotation of the sustainable development goals to construct an ecological and environmental risk warning framework. We found that in the study area, 10.51% of the land has high ecological and environmental risk and importance, corresponding to conflict zones, which require special attention. Conflict areas are mainly distributed in the Gangetic Plain in India, the plains in central and southern Cambodia, the Indonesian archipelago, and the southern coastal areas of China. Due to the uneven spatial distributions of population and important ecological and environmental resources, the pressure on this type of land use is very high. A share of 8.06% of the land has high risk–low importance, corresponding to economic development zones. Following years of human development, the ecological and environmental value of this type of land is low. A share of 58.75% of the land has low risk and importance, corresponding to wilderness areas. The natural climatic conditions of this type of land are relatively poor, often characterized by a cold climate or water scarcity, and the human interference index is low. A share of 22.68% of the land has low risk–high importance, corresponding to ecological conservation areas, which are the most important areas for ecological function services for humans at present. Finally, we proposed development suggestions for each type of land. Full article

Environmental concerns and the Paris agreements have prompted intensive efforts towards greener and more sustainable transportation. Persistent expansion of electric vehicles (EV) in the transportation sector requires electric vehicle charging stations (EVCSs) to accommodate the increased demand. Offsetting demand and alleviating the resultant electrical grid stress necessitates establishing grid-integrated renewable energy sources (RESs) where these sustainable strategies are accompanied by variable-weather-related obstacles, such as voltage fluctuations, grid instability, and increased energy losses. Strategic positioning of EVCSs and RES as distributed generation (DG) units is crucial for addressing technical issues. While technical constraints have received considerable attention, there is still a gap in the literature with respect to incorporating the additional complex optimization problems and decision-making processes associated with economic viability, social acceptance, and environmental impact. A possible solution is the incorporation of an appropriate multi-criteria decision analysis (MCDA) approach for feasible trade-off solutions. Such methods offer promising possibilities that can ease decision-making and facilitate sustainable solutions. In this context, this paper presents a review of published approaches for optimizing the allocation of renewable energy DG units and EVCSs in active distribution networks (ADNs). Promising published optimization approaches for the strategic allocation of multiple DG units and EVCSs in ADNs have been analyzed and compared. Full article

For the successful remediation of polluted sites, priority setting among the possible remediation technologies is of major importance. The related decisions are typically conditioned by a limited set of alternative remediation techniques and multiple, often contradicting criteria. These characteristics make the decision problem suitable for applying a formalised discrete multi-criteria decision analysis (MCDA). This paper reports on the outcome of a systematic review of articles published between 1995 and 2020 encompassing 43 MCDA applications to support the selection of the remediation technique for polluted soils. It focuses on the comparison between implementations of the MCDA methodology. The review identifies four gaps where progress can be made to mobilise the full strength of the MCDA methodology to support the remediation of polluted soils: (i) early stakeholder engagement, (ii) inclusion of social criteria, (iii) an informed choice of the weighting and aggregation method, (iv) and sensitivity analysis. Full article