Fuzzy Comprehensive Analytic Hierarchy Process Research Articles

Research on Driving Factors of Collaborative Integration Implementation of Lean-Green Manufacturing System with Industry 4.0 Based on Fuzzy AHP-DEMATEL-ISM: From the Perspective of Enterprise Stakeholders

The existing research and practices have shown that the coordinated implementation of lean-green manufacturing can have a positive impact on the economic and environmental benefits, which is an effective means to ensure the environmental protection of the production process of manufacturing without damaging their profitability. Within the field of lean-green research, there is still a lack of research to analyze the driving factors for the collaborative implementation of integrated lean and green integration. Although, some scholars and researchers have studied lean and green integration paradigms, their research has mostly focused on lean-green integration practices and their impact on environmental performance and their respective operations. In the context of Industry 4.0, this article investigates the driving forces behind the collaborative integration implementation of a lean-green manufacturing system from the viewpoint of stakeholders. Specifically addressing the issues of correlation and ambiguity in the identification of driving factors, this manuscript proposes an Interpretation Structure Model (ISM) of fuzzy comprehensive Analytic Hierarchy Process (AHP), based on Decision-Making Trial and Evaluation Laboratory (DEMATEL), to determine the importance of the driving factors. Combined with the complex network theory, the evaluation index system is divided into four levels from eight factor categories, including endogenous lean-green driving factors and exogenous driving factors. The fuzzy AHP-DEMATEL-ISM is used to analyze the relationship between indicators and the structure of the indicator system. The complex network which is composed of the indicator system is divided into different levels. The importance of indicators is analyzed from the perspective of the global network, and key factors affecting the driving of lean-green system is analyzed. The integration of the lean-green manufacturing system and organizational synergy are promoted to jointly lead the enterprise toward sustainable development by paying particular attention to the primary impact indicators and aggressively cultivating the key impact indicators.

Analysis of the Safety Factors of Municipal Road Undercrossing Existing Bridge Based on Fuzzy Analytic Hierarchy Process Methods

Increasing traffic volume and insufficient road lanes often require municipal roads to be reconstructed and expanded. Where a road passes under a bridge, the reconstruction and expansion project will inevitably have an impact on the bridge. To evaluate the safety impact of road engineering projects on bridges, this paper evaluates the safety of the roads and ancillary facilities of highway bridges involved in municipal road engineering projects. Based on a comprehensive analysis of the safety factors of municipal roads undercrossing existing bridges, a fuzzy comprehensive analytic hierarchy process (AHP) evaluation method for the influence of road construction on the safety of existing bridges is proposed. First, AHP is used to select 11 evaluation factors. Second, the target layer, criterion layer, and index layer of evaluation factors are established, then a safety evaluation factor system is formed. The three-scale AHP model is used to determine the weight of assessment indexes. Third, through the fuzzy comprehensive AHP evaluation model, the fuzzy hierarchical comprehensive evaluation is carried out for the safety assessment index system. Finally, the fuzzy comprehensive evaluation method is applied to the engineering example of a municipal road undercrossing an existing expressway bridge. The comprehensive safety evaluation of the existing bridge reflects the practicability and feasibility of the method. It is expected that, with further development, the method will improve the decision-making process in bridge safety assessment systems.

Research on Green Management Effect Evaluation of Power Generation Enterprises in China Based on Dynamic Hesitation and Improved Extreme Learning Machine

Carbon emissions and environmental protection issues have become the pressure from the international community during the current transitional stage of China’s energy transformation. China has set a macro carbon emission target, which will reduce carbon emissions per unit of Gross Domestic Product (GDP) by 40% in 2020 and 60–65% in 2030 than that in 2005. To achieve the emission reduction target, the industrial structure must be adjusted and upgraded. Furthermore, it must start from a high-pollution and high-emission industry. Therefore, it is of practical significance to construct a low-carbon sustainability and green operation benefits of power generation enterprises to save energy and reduce emissions. In this paper, an intuitionistic fuzzy comprehensive analytic hierarchy process based on improved dynamic hesitation degree (D-IFAHP) and an improved extreme learning machine algorithm optimized by RBF kernel function (RELM) are proposed. Firstly, we construct the evaluation indicator system of low-carbon sustainability and green operation benefits of power generation enterprises. Moreover, during the non-dimensional processing, the evaluation index system is determined. Secondly, we apply the evaluation indicator system by an empirical analysis. It is proved that the D-IFAHP evaluation model proposed in this paper has higher accuracy performance. Finally, the RELM is applied to D-IFAHP to construct a combined evaluation model named D-IFAHP-RELM evaluation model. The D-IFAHP evaluation results are used as the input of the training sets of the RELM algorithm, which simplifies the comprehensive evaluation process and can be directly applied to similar projects.