Abstract:In this paper, a stable CLSC problem is modeled in conditions of uncertainty and indeterminacy. The SCN is designed to maximize NPV and minimize carbon releases by maintaining environment friendly policies and accounting for increase. To achieve a suitable model for designing a stable CLSCN and making important decisions such as selecting the right suppliers, selecting the type of transport, initial the facility, the optimal flow between facilities and accomplishing an efficient solution to the problem decisio… Show more
“…Also, deposition, interactions and environmental conditions should not be neglected as well as influence and potential effect on human health [24][25][26][27][28]. Whether or not inhalation of PM form desert dust has adverse health effect is insufficiently investigated, there is even studies reviewed assessment of the influence of desert dust on cardiovascular diseases [29][30][31][32]. Also according to World Health Organisation (WHO) mitigation of the adverse health effects of exposure to pollutants in atmosphere has become a worldwide health concern, indicating that correlation with other research area represents challenge according to the complexity of phenomenon.…”
Forensic engineering methods might be applied in detection and identification characterisation of events according to complexity of their appearance in real environment as it covers different aspects (data, materials, chemistry, monitoring systems, technology) needed to find out the cause and predict effects. The long-distance air pollutant transport represents one challenging event for the analysis over years; specific phenomena are Saharan air masses that can transport high amounts of mineral dust particles and biological material. The dynamism of the systems in real environment, inevitably, includes time frame and spatial referencing, on location of event. However, this is directly related to providing findings and opinions when appealing to a forensic examination of an event. An example of long-distance transport of air pollutants with references to related processes in the atmosphere including time frame and spatial references is presented in the paper with discussion that is aligned with the goals of forensic engineering.
“…Also, deposition, interactions and environmental conditions should not be neglected as well as influence and potential effect on human health [24][25][26][27][28]. Whether or not inhalation of PM form desert dust has adverse health effect is insufficiently investigated, there is even studies reviewed assessment of the influence of desert dust on cardiovascular diseases [29][30][31][32]. Also according to World Health Organisation (WHO) mitigation of the adverse health effects of exposure to pollutants in atmosphere has become a worldwide health concern, indicating that correlation with other research area represents challenge according to the complexity of phenomenon.…”
Forensic engineering methods might be applied in detection and identification characterisation of events according to complexity of their appearance in real environment as it covers different aspects (data, materials, chemistry, monitoring systems, technology) needed to find out the cause and predict effects. The long-distance air pollutant transport represents one challenging event for the analysis over years; specific phenomena are Saharan air masses that can transport high amounts of mineral dust particles and biological material. The dynamism of the systems in real environment, inevitably, includes time frame and spatial referencing, on location of event. However, this is directly related to providing findings and opinions when appealing to a forensic examination of an event. An example of long-distance transport of air pollutants with references to related processes in the atmosphere including time frame and spatial references is presented in the paper with discussion that is aligned with the goals of forensic engineering.
“…In contrast, finally, Moradi and Sangari (40) outlined a multi-level supply chain network, accounting for uncertain parameters and employing robust optimization techniques to mitigate fixed and transportation costs. Kalantari et al (41)employed a fuzzy robust stochastic optimization approach to reduce environmental impacts while maximizing net present value and social impacts within a sustainable closed-loop supply chain. In recent years, several mathematical models have emerged in the field of closed-loop supply chain management.…”
Recently, the difference in the most effective competencies is considered the main competitive factor in organizations. To this end, organizations seek to improve a number of their functional capabilities, expertise, and capacities to enhance their operational area. Therefore, when an organization focuses on the quality of its services or products, it is trying to improve maintainability to gain a competitive advantage. In this study, a closed-loop, multi-objective, multi-level, multi-commodity, and multi-period mathematical model for a supply chain with producer, and distributor components is presented to locate and allocate items. The presented model can control environmental, economic, and social factors along the chain. One of the most important and unique aspects of the current study is considering different scenarios in the closed-loop supply chain (CLSC) so that the quality of the produced and transported products is paid attention to according to perishability. In addition, to control environmental effects, the model can minimize total CO2 emissions. The problem is solved on small, medium, and large scales using Epsilon Constraint and NSGA-II methods. According to the obtained results, the flow according to the boom scenario is more than the stagnation scenario. Finally, according to the sensitivity analysis, the number of centers established increases with an increase in demand. The results show that the nondominated sorting genetic algorithm (NSGA-II) model can predict the behavior of the model well in the long term. For this purpose, Mean ideal distance (MID) index, has been used for evaluation of calculation. the value of standard MID is equal to 6.56 that shows the model accuracy is adequate.
“…Wang et al (2010) introduced single-valued neutrosophic sets (SVNSs), which are considered as an extension of neutrosophic sets. Moreover, various extensions of neutrosophic sets, such as interval neutrosophic sets (Liu et al, 2022;Wang et al, 2005), trapezoidal neutrosophic sets (Liang et al, 2018b;Sarma et al, 2019), type-2 neutrosophic sets (Gokasar et al, 2022), multi-valued neutrosophic sets (MVNSs) (Ji et al, 2018;Ye et al, 2022), probability MVNSs (Liu and Cheng, 2019;, interval-valued fermatean neutrosophic sets (Broumi et al, 2022) and complex fermatean neutrosophic sets (Broumi et al, 2023) have been proposed and applied to address various neutrosophic multi-criteria decision making (MCDM) problems, such as investment decision, personnel selection, disaster management and designing a stable sustainable closed-loop supply chain network (Kalantari et al, 2022). Among various forms of neutrosophic sets, SVNSs are considered as one of the most concise tools to capture DMs' evaluations (Peng and Dai, 2020).…”
In practical linguistic multi-criteria group decision-making (MCGDM) problems, words may indicate different meanings for various decision makers (DMs), and a high level of group consensus indicates that most of the group members are satisfied with the final solution. This study aims at developing a novel framework that considers the personalized individual semantics (PISs) and group consensus of DMs to tackle linguistic single-valued neutrosophic MCGDM problems. First, a novel discrimination measure for linguistic single-valued neutrosophic numbers (LSVNNs) is proposed, based on which a discrimination-based optimization model is built to assign personalized numerical scales (PNSs). Second, an extended consensus-based optimization model is constructed to identify the weights of DMs considering the group consensus. Then, the overall evaluations of all the alternatives are obtained based on the LSVNN aggregation operator to identify the ranking of alternatives. Finally, the results of the illustrative example, sensitivity and comparative analysis are presented to verify the feasibility and effectiveness of the proposed method.
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