Effective coordination of operational decisions is critical in today’s global supply chains, where businesses face evolving regulations and changing consumer preferences. Large logistics providers must efficiently manage distribution networks, often through vendor-managed inventory (VMI) systems. In VMI, suppliers control customer inventories, deciding delivery timing and quantities to optimize freight consolidation and routing. This thesis develops optimization algorithms to address two VMI-related problems, where suppliers schedule deliveries to multiple customers to prevent stockouts while minimizing travel and inventory costs.nnThe first problem focuses on a two-echelon distribution network, leading to the two-echelon inventory routing problem (2E-IRP). Freight moves from depots to intermediate satellites via large vehicles and then to customers via smaller vehicles. A branch-and-price (BP) algorithm with novel acceleration techniques and branching rules is proposed. Computational results on 400 instances show optimal solutions for 149 cases, near-optimal solutions for 77, and reasonable bounds for the remainder. A matheuristic based on tabu search and mathematical programming is introduced to solve larger instances efficiently, often outperforming the exact BP algorithm.nnThe second problem, the inventory routing problem with time windows (IRPTW), considers direct deliveries from depots to customers under strict service time windows. A branch-price-and-cut (BPC) algorithm is developed using a combined path-flow and two-commodity flow formulation, outperforming a state-of-the-art benchmark on larger instances.