Resilient-Sustainable Supplier Selection and Order Allocation

Wu Yuanjun

Abstract

This research focuses on integrating sustainability and resilience into traditional supplier selection and order allocation processes. By leveraging the Random Forest Regression and MARCOS method, a comprehensive supplier evaluation system is developed, which can accurately assess and rank suppliers. The order allocation model, constructed through multi - objective programming and solved using the Genetic Algorithm, takes into account cost, quality, delivery, and supplier sustainability and resilience. This provides a scientific basis for enterprise procurement decisions. The model's accuracy and robustness are verified through real - world examples, showing its effectiveness in helping enterprises optimize procurement decisions and enhance supply chain competitiveness. However, the research has limitations, and future work can explore index optimization and dynamic model adjustment to better adapt to different industries and market changes.

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