An Improved Hybrid Grey Relational Analysis Approach for Green Resilient Supply Chain Network Assessment

Abstract

In the growing and turbulent market of the current world both in national and in international relations, the need for reviewing and assessment of the resiliency of suppliers as one of the new concepts in supply chain management has been prioritized. In addition, globalization, increasing the regulations of governmental and non-governmental organizations, customers' request and pressure regarding environmental issues has led organizations to evaluate the measures necessary to implement green supply chain management, to improve their environmental and economic performance. The subject of selecting and evaluating suppliers on green supply chain with resilience capability first requires the identification of the supplier evaluation criteria so that it considers the resiliency of the supply chain concurrent with the concepts of green supply chain. Secondly, right tools should be used for the decision. Considering all the criteria and indicators in conditions of uncertainty encourages the development and application of methods, such as fuzzy theory and grey systems theory. In this research, a comprehensive model for evaluating green resilience supply chain network is provided. In order to apply both quantitative and qualitative criteria, the possibility of making the target based criteria dimensionless along the cost or benefit criteria, the use of experts' opinions in the allocation of weights to the criteria and indicators using grey numbers, grey relational analysis are developed and improved. In the end, the implementation of the proposed model is explained step by step in a case study and the future conclusions and recommendations are suggested.

Safety Assessment of Casting Workshop by Cloud Model and Cause and Effect–LOPA to Protect Employee Health

“…The cloud model [22][23][24] was introduced to take randomness into consideration, the integrated weight method [33] was adopted, and a new algorithm was proposed to determine the preference coefficient of the integrated weight based on the least square method [35] in this study. To validate the cloud model and integrated weight algorithm for the safety assessment, grey relational analysis [16][17][18] was applied. Then, the causes and sub-causes of dangerous and harmful factors were identified by cause and effect analysis [36,37], and the causes mainly including dust, noise, toxic gas, mechanical injury, empyrosis and electric shock.…”

“…Frequently used safety assessment methods include fuzzy evaluation [13][14][15], grey relational analysis [16][17][18], neural network [19][20][21], and the cloud model [22][23][24]. To better evaluate various failure modes, a new fuzzy hybrid model to analyze failure modes and effects was proposed by Fattahi and Khalilzadeh [13], in which a fuzzy weight risk priority was considered for each failure.…”

A Hybrid Multi-Criteria Decision-Making Model for Evaluating Companies’ Green Credit Rating

“…The GRA is used to select the representative financial ratios for the three categories to measure the companies' financial performances [56]. The main reason for choosing the GRA is its computational flexibility, the small amount of data and the uncertainty of the distribution type of the data [57,58]. In the grey theory, there are two kinds of Step 1: Apply GRA to measure the degree of correlation between the indicators.…”

Optimization of Scanning Parameters in Coordinate Metrology Using Grey Relational Analysis and Fuzzy Logic

“…The remarkable characteristics about grey theory are its capability to overcome the inconclusiveness and confusion of human decisions through mathematical protocol or language. The GRA exhibits numerous benefits, including satisfactory results with lesser data and computational simplicity, [31,32]. It is especially useful when the experiments cannot be performed precisely and it aids to compensate the limitations in statistical regression [33].…”