A Mathematical Model for Resilience Supply Chain Network Design in Uncertainty Approach

This research paper presents a comprehensive mathematical model for designing resilient supply chain networks under uncertainty. The model incorporates various factors that contribute to supply chain resilience, such as demand variability, disruptions, and supply chain complexity. By considering these elements, the model aims to optimize the network structure and decision-making processes to enhance its ability to withstand shocks and maintain operations during challenging times. The study begins with a thorough literature review that examines existing research on supply chain resilience and mathematical modeling techniques. Subsequently, a novel mathematical model is developed, incorporating key resilience metrics and decision variables. The model is then solved using advanced optimization algorithms to determine optimal network configurations. Numerical experiments are conducted to evaluate the performance of the proposed model. Different scenarios are simulated to assess the model's sensitivity to various uncertainties and its effectiveness in mitigating risks. The results demonstrate the model's capability to design resilient supply chains that can adapt to changing conditions and minimize disruptions. Finally, the paper concludes by summarizing the essential findings and contributions of the research. The limitations of the study are also discussed, along with potential avenues for future research.This research paper presents a comprehensive mathematical model for designing resilient supply chain networks under uncertainty. The model incorporates various factors that contribute to supply chain resilience, such as demand variability, disruptions, and supply chain complexity. By considering these elements, the model aims to optimize the network structure and decision-making processes to enhance its ability to withstand shocks and maintain operations during challenging times. The study begins with a thorough literature review that examines existing research on supply chain resilience and mathematical modeling techniques. Subsequently, a novel mathematical model is developed, incorporating key resilience metrics and decision variables. The model is then solved using advanced optimization algorithms to determine optimal network configurations. Numerical experiments are conducted to evaluate the performance of the proposed model. Different scenarios are simulated to assess the model's sensitivity to various uncertainties and its effectiveness in mitigating risks. The results demonstrate the model's capability to design resilient supply chains that can adapt to changing conditions and minimize disruptions. Finally, the paper concludes by summarizing the essential findings and contributions of the research. The limitations of the study are also discussed, along with potential avenues for future research.

Keywords:

Resilience , Supply Chain , Network Design , Mathematical Model