In the era of internet connection and IOT, data-driven decision-making has become a new trend of decision-making and shows the characteristics of multi-granularity. Because three-way decision-making considers the uncertainty of decision-making for complex problems and the cost sensitivity of classification, it is becoming an important branch of modern decision-making. In practice, decision-making problems usually have the characteristics of hybrid multi-attributes, which can be expressed in the forms of real numbers, interval numbers, fuzzy numbers, intuitionistic fuzzy numbers and interval-valued intuitionistic fuzzy numbers (IVIFNs). Since other forms can be regarded as special forms of IVIFNs, transforming all forms into IVIFNs can minimize information distortion and effectively set expert weights and attribute weights. We propose a hybrid multi-attribute three-way group decision-making method and give detailed steps. Firstly, we transform all attribute values of each expert into IVIFNs. Secondly, we determine expert weights based on interval-valued intuitionistic fuzzy entropy and cross-entropy and use interval-valued intuitionistic fuzzy weighted average operator to obtain a group comprehensive evaluation matrix. Thirdly, we determine the weights of each attribute based on interval-valued intuitionistic fuzzy entropy and use the VIKOR method improved by grey correlation analysis to determine the conditional probability. Fourthly, based on the risk loss matrix expressed by IVIFNs, we use the optimization method to determine the decision threshold and give the classification rules of the three-way decisions. Finally, an example verifies the feasibility of the hybrid multi-attribute three-way group decision-making method, which provides a systematic and standard solution for this kind of decision-making problem.
Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.
Many application fields initiate using wireless sensor network (WSN), and the evaluation for its performance becomes an important topic, which can help the decision-maker to find the deficiency of the current WSN or seek the best WSN. There exist mixed multiple attributes in the WSN performance evaluation process, for example, some evaluation indicators can be expressed as interval numbers, while others can be expressed as linguistic variables, so it is necessary to explore the evaluation model based on mixed multiattribute decision-making (MADM). Considering the specific evaluation purpose and requirements for different enterprises, this paper puts forward an indicator selection method and a subjective weighting method based on the rough set theory. After that, based on the transformation of mixed attributes into the unified intuitionistic fuzzy numbers (IFNs), an objective weighting method based on intuitionistic fuzzy entropy is proposed. Meanwhile, the combined weights of indicators are obtained by synthesizing the subjective and objective weights. Subsequently, in order to evaluate WSN performance objectively, an integrated comprehensive evaluation framework is proposed, which includes single evaluation, compatibility test, combination evaluation, and consistency test. The paper gives specific models and calculation steps in detail. Finally, it provides a case study to explain the application of the proposed indicator selection method and the evaluation models, which provide new ideas and references for WSN performance evaluation.
Energy consumption is an important source of the emissions of CO2 and air pollutants such as SO2 and NOX. Reducing energy consumption can realize the simultaneous reduction of air pollutants and CO2 emissions to a certain extent. This study examines the collaborative allocation of energy consumption and the emissions of SO2, NOX and CO2 in China. In contrast to previous studies, this paper proposes an improved centralized DEA model that takes into account the correlation between energy consumption and air environmental emissions, the economic development demand and the energy resource endowment of different provinces. The initial allocation scheme is obtained based on the principle of equity. Then, the initial allocation results are brought into the improved centralized DEA model to maximize the expected output. The empirical analysis of projected data for 2025 shows that the looser the restrictions of energy consumption, the greater the optimal economic output. When the energy consumption of each province is allowed to fluctuate within the range of 85% to 115% of the initial quota, the total GDP is the largest and 20.62% higher than the initial GDP. The optimal allocation scheme is more equitable than the initial scheme and realizes absolute interpersonal equity and economic equity. Eighteen provinces bear the pressures of energy saving, emission reduction or GDP growth, with average pressure indexes of 11.46%, 16.85% and 40.62%, respectively. The pressures on the major regions involved in the “Belt and Road”, Beijing-Tianjin-Hebei region and Yangtze River Economic Belt national strategies will thus be reduced significantly; the maximum pressures on energy saving, emission reduction and GDP growth are 10.03%, 12.17% and 29.84%, respectively. China can take a series of measures to promote regional coordinated development and improve the realization of optimal allocation schemes, including establishing unified resource asset trading platforms, improving the methods of regional cooperation, building effective transportation and logistics transport networks to weaken the barriers among regions and implementing differentiated regional policies and regional interest coordination mechanisms.
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