In multiattribute large-group decision-making (MALGDM), the ideal state indicates a high degree of consensus for decision-makers. However, it is difficult to reach a consensus because the conflict between various decision attributes and decision-makers increases. To deal with the problem, a novel consensus model was developed to manage the decision-making in large groups based on noncooperative behavior. The improved clustering method was used to take account of the similarities among different decision-makers, while similar decision-makers will be grouped into the same group. Moreover, the consensus threshold was determined from an objective and subjective aspect to judge whether the consensus reaching process continues. The noncooperative behavior and adjustment amount of decision-makers’ opinions were investigated based on the proposed consensus model, and an emergency decision-making problem in flood disaster is applied to manifest the feasibility and distinctive features of the proposed method. The results show the proposed novel consensus model demonstrated strong applicability and reliability to the noncooperative subgroup problem and can be explored to manage multiattribute interactions in LGDM.
In multi-attribute large group decision-making (MALGDM), the ideal state indicates a high degree of consensus among a set of decision-makers (DMs). It is complex to reach consensus because the number of decision attributes and DMs increases. Thus, we developed a novel consensus model to manage the decision-making in large group based on the non-cooperative behavior. The improved clustering method takes account of the similarities among different DMs. Similar DMs will be grouped into the same group. The consensus threshold is determined from an objective and subjective aspect to judge whether the consensus reaching process continues. With the introduction of three non-cooperative behaviors, we investigated a non-cooperative behavior detection method under the change of consensus level. Base on the number of DMs who are willing to change their preliminary views and the change value of consensus level, the non-cooperative degree of subgroup can be computed. According to the non-cooperative degree, the subgroups’ weight can be modified to raise the consensus level. Meanwhile, the subgroup is allowed to change. Based on the adjustment amount of DMs’ opinions, whether decision maker (DM) belongs to this subgroup is recalculated. Finally, an emergency decision-making problem in flood disaster is applied to manifest the feasibility and distinctive features of the proposed method.
The development of the tourism industry has led to increased pressure of people flow in tourist blocks. Therefore, it is critical to ease the traffic pressure in these blocks. This paper aims to identify the bottleneck links of street networks in tourist blocks to achieve the effective prevention of congestion accidents. A logit stochastic user equilibrium model combined with spatial syntax is presented to study the travelers’ route choice behavior. The nonlinear Bureau of Public Roads function is applied to calculate the time impedance of each street. A case analysis of the Chongqing Ciqikou tourist block shows that the bottleneck link has the features of high integration and a large degree of negative time impedance evolution. The research’s results are more consistent with practical circumstances because the influence of the road network topological structure on pedestrian path selection has been considered.
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