APPLICATIONS OF ROBUST OPTIMIZATION IN LOGISTIC MANAGEMENT

Abstract

In the past few decades, the market of logistic management develops rapidly due to the expansion of e-commerce and the increasing complexity of the supply chain system. As a critical component in trading activities, logistic management contributes a significant amount of total management cost, and thus the related optimization methods are widely concerned by industrial practitioners and academic researchers. A minor improvement of the strategic plan can introduce a large amount of cost reduction due to the scale of the system, and therefore exact approaches that identify the optimal solution within a reasonable amount of time are preferred. Moreover, the uncertainty is ubiquitous in the real world. A priori decision ignoring the uncertainty may not be valid after the realization of uncertain factors, and the robustness of the decision should be assessed in the prescriptive analysis. This thesis is motivated by these concerns in the logistic management context, and aims to demonstrate possible practices of robust optimization approach in real-world applications.