Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.     

基于PROMETHEEⅡ法的污染场地土壤修复技术筛选及应用

依据当前污染场地土壤修复技术特点以及场地特征,构建4层12指标21方案的污染土壤修复技术决策分析结构,运用多属性决策分析方法——PROMETHEEⅡ偏好排序法,对当前场地修复技术以及典型场地条件进行了客观分析和综合评价,实现基于具体修复目标的污染场地土壤修复技术择优筛选,并采用该方法对虚拟特定污染场地的土壤修复技术筛选进行了实例应用。这为污染场地的治理和修复提供了方法依据和理论参考。     

Collaborative environmental planning in river management: an application of multicriteria decision analysis in the White River Watershed in Vermont

Multicriteria decision analysis (MCDA) provides a well-established family of decision tools to aid stakeholder groups in arriving at collective decisions. MCDA can also function as a framework for the social learning process, serving as an educational aid in decision problems characterized by a high level of public participation. In this paper, the framework and results of a structured decision process using the outranking MCDA methodology preference ranking organization method of enrichment evaluation (PROMETHEE) are presented. PROMETHEE is used to frame multi-stakeholder discussions of river management alternatives for the Upper White River of Central Vermont, in the northeastern United States. Stakeholders met over 10 months to create a shared vision of an ideal river and its services to communities, develop a list of criteria by which to evaluate river management alternatives, and elicit preferences to rank and compare individual and group preferences. The MCDA procedure helped to frame a group process that made stakeholder preferences explicit and substantive discussions about long-term river management possible.     

Multicriteria ranking of workplaces regarding working conditions in a mining company

Ranking of workplaces with respect to working conditions is very significant for each company. It indicates the positions where employees are most exposed to adverse effects resulting from the working environment, which endangers their health. This article presents the results obtained for 12 different production workplaces in the copper mining and smelting complex RTB Bor – ‘Veliki Krivelj’ open pit, based on six parameters measured regularly which defined the following working environment conditions: air temperature, light, noise, dustiness, chemical hazards and vibrations. The ranking of workplaces has been performed by PROMETHEE/GAIA. Additional optimization of workplaces is done by PROMETHEE V with the given limits related to maximum permitted values for working environment parameters. The obtained results indicate that the most difficult workplace is on the excavation location (excavator operator). This method can be successfully used for solving similar kinds of problems, in order to improve working conditions.     

Dominance based fuzzy decision support framework for g-resilient (ecosilient) supplier selection: an empirical modelling

A novel decision support framework has been proposed herein to solve supplier selection problems by considering green as well as resiliency criteria, simultaneously. An expert team involving a finite number of Decision-Makers (DMs) is to be employed to obtain degree of importance of each of the evaluation criteria and also to assign an appropriate rating for each supplier alternative with respect to the criteria. Since subjective human judgment often bears some sort of ambiguity as well as vagueness, application of fuzzy set theory can be recommended in this context. The present work represents a dominance based decision support system in the light of fuzzy set theory which is basically a simplified version of TODIM and PROMETHEE. It explores dominance between two alternatives with respect to a particular criterion, based on which a global dominance measure is computed to facilitate ranking order of candidate suppliers. The approach proposed in this research seems straightforward which can exclude complex and tedious computational steps of TODIM as well as PROMETHEE. Application potential of the proposed dominance based fuzzy decision-making approach has been compared to that of Fuzzy-TOPSIS and Fuzzy-VIKOR. Good agreement has been observed. In addition to this, the concept of a unique performance index i.e. ‘g-resilient’ (also called ‘ecosilient’) index has been introduced to help in assessing suppliers’ overall performance extent. The work has also been extended to identify the ill (poor)-performing areas in which suppliers are lagging and seek further improvement towards enhancing g-resilient performance level.     

Identification of Areas in Brazil that Optimize Conservation of Forest Carbon,Jaguars, and Biodiversity

A major question in global environmental policy is whether schemes to reduce carbon pollution through forest management, such as Reducing Emissions from Deforestation and Degradation (REDD+), can also benefit biodiversity conservation in tropical countries. We identified municipalities in Brazil that are priorities for reducing rates of deforestation and thus preserving carbon stocks that are also conservation targets for the endangered jaguar (Panthera onca) and biodiversity in general. Preliminary statistical analysis showed that municipalities with high biodiversity were positively associated with high forest carbon stocks. We used a multicriteria decision analysis to identify municipalities that offered the best opportunities for the conservation of forest carbon stocks and biodiversity conservation under a range of scenarios with different rates of deforestation and carbon values. We further categorized these areas by their representativeness of the entire country (through measures such as percent forest cover) and an indirect measure of cost (number of municipalities). The municipalities that offered optimal co‐benefits for forest carbon stocks and conservation were termed REDDspots (n = 159), and their spatial distribution was compared with the distribution of current and proposed REDD projects (n = 135). We defined REDDspots as the municipalities that offer the best opportunities for co‐benefits between the conservation of forest carbon stocks, jaguars, and other wildlife. These areas coincided in 25% (n = 40) of municipalities. We identified a further 95 municipalities that may have the greatest potential to develop additional REDD+ projects while also targeting biodiversity conservation. We concluded that REDD+ strategies could be an efficient tool for biodiversity conservation in key locations, especially in Amazonian and Atlantic Forest biomes. Identificación de Áreas en Brasil que Optimizan la Conservación del Carbono del Bosque, Jaguares y la Biodiversidad.