INTEGRATING GRAPH-THEORETIC METHODS INTO TRANSPORTATION LOGISTICS: A COST-MINIMIZATION APPROACH

Abstract

The transportation problem remains a central concern in logistics and operations research, aimed at determining the most efficient way to move goods from sources to destinations while minimizing cost. This study explores the integration of graph-theoretic methods into transportation logistics, providing a robust mathematical framework for analyzing and solving complex transport networks. By modeling transportation systems as weighted graphs and applying tools such as shortest path algorithms, minimum spanning trees, and minimum-cost flow models, this approach offers deeper insights into cost minimization, network resilience, and operational efficiency. Additionally, the application of regularization techniques enhances solution stability and robustness. The study concludes that graph-based frameworks are not only mathematically sound but also practically advantageous for modern logistics planning.