Resilient supply chain optimization

Abstract

Especially after the COVID -19 the importance of studying the about resilient supply chain optimization has been increased even more. A supply chain network can be optimized with respect to many aspects such as inventory, supplier management and warehousing etc. In this study, the objective was to optimize the resilience in supply chain network with respect transportation cost and connectivity under different disruption scenarios. Since this study was based on hypothetical problem, after developing the relevant data, linear mathematical model and a mixed integer mathematical model was developed to achieve the research goal. The research modelling has done in two parts, where first part will solely focus on minimizing the transportation cost using linear mathematical model and in the second part minimizing transportation cost, considering the density of connections has been modeled using a mixed integer mathematical model.

The results of both modeling, along with sensitivity and scenario analysis shows that demand volatility has much more impact on the transportation cost compared to other disruption scenarios that was considered. It is further showed that compared to the original optimized model, the number of connections has been increased under the disruption but throughout the simulations the total number of connectivity remains to be unchanged. Overall, the thesis provides an idea about how the suggested solution would help the model to be more resilient.