The recent developments and innovations in computational methods tailored for solving largescale
optimization problems inherent in the domains of logistics and supply chain management.
As these industries grapple with the challenges of increasing complexity, globalization, and the
need for real-time decision-making, the demand for efficient optimization techniques has
grown significantly. The paper delves into the theoretical foundations of optimization
algorithms, their implementation details, and their practical applications in optimizing various
facets of logistics and supply chain networks.
Keywords: Large-Scale Optimization, Logistic and Supply Chain Management, Computational
Methods, Convex Optimization, Machine Learning