How to facilitate collaborative development between the enterprise and the environment under the dual constraints of resources and the environment is the focus of today's green supply chain management system research. Through the performance evaluation of the green supply chain, we can understand the operation of the whole supply chain and its shortcomings, provide a basis for improving related processes, and have important practical significance for improving the competitiveness and protection of its products. First of all, by summarising and analysing the research status of sustainable supply chain management in different countries, the research idea and overall background of this paper are proposed. It discusses the theory of sustainable supply chain management and the performance evaluation system and calculation types of sustainable supply chain management. Finally, the relative weight of each index is determined based on the sustainability calculation method, and then the decentralisation degree of the index is constructed. During this period, the fuzzy comprehensive evaluation method is used to evaluate the performance of sustainable supply chain, conduct case analysis and summary, and evaluate the performance of green supply chain component in economic, social, environmental and other aspects. In this paper, representative companies are selected as examples to evaluate their green supply chain management performance, and the evaluation algorithm is studied based on sustainable calculation method. The results show that a reasonable and effective evaluation of the enterprise performance of green supply chain management and a sustainable algorithm study can effectively identify potential problems in the operation of the company and improve the overall operation of the company at this stage.
Due to global pandemics, political unrest and natural disasters, the stability of the supply chain is facing the challenge of more uncertain events. Although many scholars have conducted research on improving the resilience of the supply chain, the research on integrating product family configuration and supplier selection (PCSS) under disruption risks is limited. In this paper, the centralized supply chain network, which contains only one major manufacturer and several suppliers, is considered, and one resilience strategy (i.e., the fortified supplier) is used to enhance the resilience level of the selected supply base. Then, an improved stochastic bi-objective mixed integer programming model is proposed to support co-decision for PCSS under disruption risks. Furthermore, considering the above risk-neutral model as a benchmark, a risk-averse mixed integer program with Conditional Value-at-Risk (CVaR) is formulated to achieve maximum potential worst-case profit and minimum expected total greenhouse gases (GHG) emissions. Then, NSGA-II is applied to solve the proposed stochastic bi-objective mixed integer programming model. Taking the electronic dictionary as a case study, the risk-neutral solutions and risk-averse solutions that optimize, respectively, average and worst-case objectives of co-decision are also compared under two different ranges of disruption probability. The sensitivity analysis on the confidence level indicates that fortifying suppliers and controlling market share in co-decision for PCSS can effectively reduce the risk of low-profit/high-cost while minimizing the expected GHG emissions. Meanwhile, the effects of low-probability risk are more likely to be ignored in the risk-neutral solution, and it is necessary to adopt a risk-averse solution to reduce potential worst-case losses.
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