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A major challenge in flood mapping using multi‐criteria decision analysis (MCDA) is the selection of the flood risk factors and the estimation of their relative importance. A novel MCDA method through the integration of two state‐of‐the‐art MCDA methods based on catastrophe and entropy theory is proposed for mapping flood risk in the Peninsular Malaysia, an area very susceptible to flooding events, is presented. A literature review was undertaken which identified the various socioeconomic, physical and environmental factors which can influence flood vulnerability and risk. A set of variables was selected using an importance index which was developed based on a questionnaire survey. Population density, percentage of vulnerable people, household income, local economy, percentage of foreign nationals, elevation and forest cover were all deemed highly relevant in mapping flood risk and determining the zones of maximum vulnerability. Spatial integration of factors using the proposed MCDA revealed that coastal regions are highly vulnerable to floods when compared to inland locations. Flood risk maps indicate that the northeastern coastal region of Malaysia is at greatest risk of flooding. The prediction capability of the integrated method was found to be 0.93, which suggests good accuracy of the proposed method in flood risk mapping.

Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well.

The construction sector plays an important role in a country’s economic development. The financial performance of a company is a good indicator of its financial health and status. In Malaysia, the government encourages the construction industry to develop an advanced infrastructure related to health, transport, education and housing. In view of the COVID-19 pandemic, the operations and financial performance of construction sector companies have been affected recently. Additionally, uncertainty plays a vital role in the multi-criteria decision-making (MCDM) process. Based on previous studies, there has been no comprehensive study conducted on the evaluation of the financial performance of construction companies by integrating entropy and fuzzy VIKOR models. Therefore, this paper aims to propose an MCDM model to evaluate and compare the financial performance of construction companies with an integrated entropy–fuzzy VIKOR model. A case study is carried out by evaluating the listed construction companies in Malaysia with the proposed model. The findings of this paper indicate that the company ECONBHD achieves the best financial performance over the study period. The significance of this paper is to determine the priority of the financial ratios and ranking of the construction companies with the proposed entropy–fuzzy VIKOR model.

Floods are natural disasters with significant socio-economic consequences. Urban areas with uncontrolled urban development, rapid population growth, an unregulated municipal system and an unplanned change of land use belong to the highly sensitive areas where floods cause devastating economic and social losses. The aim of this paper is to present a reliable GIS multi-criteria methodology for hazard zones’ mapping of flood-prone areas in urban areas. The proposed methodology is based on the combined application of geographical information systems (GIS) and multi-criteria decision analysis (MCDA). The methodology considers six factors that are relevant to the hazard of flooding in urban areas: the height, slope, distance to the sewage network, the distance from the water surface, the water table and land use. The expert evaluation takes into account the nature and severity of observed criteria, and it is tested using three scenarios: the modalities of the analytic hierarchy process (AHP). The first of them uses a new approach to the exploitation of uncertainty in the application of the AHP technique, the interval rough numbers (IR’AHP). The second one uses the fuzzy technique for the exploitation of uncertainty with the AHP method (F’AHP), and the third scenario contemplates the use of the traditional (crisp) AHP method. The proposed methodology is demonstrated in Palilula Municipality, Belgrade, Serbia. In the last few decades, Palilula Municipality has been repeatedly devastated by extreme flood events. These floods severely affected the transportation networks and other infrastructure. Historical flood inundation data have been used in the validation process. The final urban flood hazard map proves a satisfactory agreement between the flood hazard zones and the spatial distribution of historical floods that happened in the last 58 years. The results indicate that the scenario in which the IR’AHP methodology is used provides the highest level of compatibility with historical data on floods. The produced map showed that the areas of very high flood hazard are located on the left Danube River bank. These areas are characterized by lowland morphology, gentle slope, sewage network, expansion of impermeable locations and intense urbanization. The proposed GIS-IR’AHP methodology and the results of this study provide a good basis for developing a system of flood hazard management in urban areas and can be successfully used for spatial city development policy.

Summary In this paper, the multiple objectives optimization problem in a finite‐state model predictive control (FS‐MPC) is formulated using fuzzy multi‐criteria decision‐making. Conventionally, to optimize the multiple objectives in a FS‐MPC, the aggregate objective function or a single cost function is constructed, which requires the weighting factor tuning to select the appropriate switching state. Determination of these weighting factors for a particular objective function is a complex and time‐consuming task as no systematic procedure is available in literature. The main aim of this paper is to replace the time‐consuming task of weighting factor tuning by a simple and systematic procedure, which relies on the relative importance of the individual objective functions. The relative importance of objective functions derived from the expert's knowledge and the desired control objectives is used for appropriate switching state selection. The method is validated with the help of simulation results of a neutral point clamped inverter for the multiple objectives viz. reference current tracking, capacitor voltage balance and switching frequency minimization. The result outcomes of the proposed methodology are compared with the conventional FS‐MPC and space vector pulse width modulation based current control schemes. Copyright © 2014 John Wiley & Sons, Ltd.

Under the global implementation of a low-carbon economy, the treatment of municipal plastic solid waste (PSW) has become an important task to be solved urgently. In the actual decision-making process of PSW treatment, the evaluation information is usually fuzzy, and the decision-makers (DMs) are bounded rational. For selecting the most appropriate PSW treatment technology, we propose a multi-criteria decision-making (MCDM) method based on cumulative prospect theory and fuzzy decision-making trail and evaluation laboratory (DEMATEL). Firstly, we construct the criteria system of PSW treatment that consists of 9 sub-criteria from the perspectives of environment, economy, society, and technology. Then, considering the interdependences and interactions between these evaluation criteria and allowing multiple stakeholders to participate in decision-making, we propose a fuzzy DEMATEL method to deal with the fuzziness of evaluation in the decision-making process and determine the weights of the evaluation criteria. Subsequently, taking into account the different opinions of different stakeholders and psychological factors such as risk preference and loss aversion of stakeholders, we aggregate the evaluation information of different stakeholders and develop the PSW treatment alternatives to rank the orders by using the proposed multi-actor cumulative prospect theory (CPT) method. We study seven alternative processes for PSW treatment by the developed model, including landfill, recycling, pyrolysis, incineration, and the combination of landfilling and recycling, landfill and incineration, and recycling and pyrolysis. According to the ranking results, we find the combination of recycling and incineration is the best treatment alternative. We take the seven PSW treatment technologies in Shanghai as the case study to verify the effectiveness and feasibility of the proposed method. Through the sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method, we illustrate the effectiveness and superiority of the proposed method. This research provides significant references for the PSW treatment technology selection problems under uncertain environments and extends the methods in the decision-making field.

Due to rapid urbanization and the resulting rapid population increases, an important problem for cities today is the elimination of solid waste or finding suitable places for waste storage. Municipal solid waste disposal (MSWD) site selection is one of the most important steps in urban waste management. Many criteria political, economic, social, and technological should be considered in this process. Geographic information systems (GIS) and multi-criteria decision-making (MCDM) are tools that are superior to traditional methods in the planning phase of site selection studies. In this study, suitable MSWD sites were determined in Mersin (a Turkish province) based on GIS and the analytic hierarchy process, an MCDM method. Unsuitable areas in the study were removed at the beginning of the analysis. Eleven evaluation criteria were selected: elevation, slope, permeability, distance from lineaments, groundwater level, distance from rivers and water surfaces, distance from roads, distance from settlements, distance from protected areas, and land cover. Considering the evaluation and exclusion criteria, 19.12% of the study area was deemed suitable, and 80.88% was determined unsuitable for an MSWD site. An MSWD suitability map was created as a result of the study. The outcomes indicate that 80,377 ha and 83,022 ha of the study area were classified as high and very high suitability, respectively. Based on these results, we evaluate whether the locations of existing solid waste landfills are appropriate and propose alternative solid waste landfills for each district.

Regarding hard situations like war, the increasing cost of extraction and exploration of fossil fuels make governments move toward green and clear renewable energy (RE). As a result, we propose a novel multi-criteria decision-making (MCDM) method for RE location (REL) for the first time. This model suggests a Robust, Resilience MCDM with Risk approach (RRMCDMR) for REL. We propose a risk approach by adding a risk function in MCDM. A robust convex approach is used to tackle the uncertainty of the model for the real world. We compare the RRMCDMR problem in a wind farm location in Iran with different risk coefficient functions. As defined, Khaf, Nehbandan, and Esfarayan are in locations one to three in all modes. We changed the normalized risk function and suggested two other risk functions that can help risk-averse and risk-neutral decision-makers. We varied the robust convex coefficient and considered that by increasing the robust convex coefficient, the alternative score increased.

The effects of urban transport are highly concerning. The rapid urbanization and motorization in smart cities have a huge impact on sustainability. The goal of the paper is to analyse the smart cities selected, in terms of the urban transport. This paper presents an overview of research works published between 1991 and 2020 concerning urban transport and MCDM (multi-criteria decision making). The author highlights the importance of decision-making criteria and their weight, as well as techniques. Seven criteria and forty-four objects were used as the input of the approach. The entropy weight method was used to compute the weight of each criterion. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was applied to calculate the assessment and ranking of transport performance for each smart city. Portland was found to be the best location for transport enterprises and projects; Tbilisi was ranked last. The values of the relative closeness coefficient ranged from 0.03504 to 0.921402. Finally, some suggestions for future research are discussed.