This literature-based analytical study examines milk distribution network optimization as an application of operations research, with particular attention to the Milk Collection Problem and its relationship to classical transportation and vehicle-routing models. Two peer-reviewed studies published in 2022 are comparatively examined. The first investigates a Milk Collection Centre–Vehicle Routing Problem for a dairy operation in southern Chile, integrating facility-location decisions with vehicle routing and separate milk-quality constraints. The second develops a Milk Collection Problem model for a real dairy company in Turkey, incorporating heterogeneous vehicle capacities, time windows, vehicle-access restrictions, milk-quality incompatibility, tank loading requirements, and fuel-consumption effects. The study compares the modelling structures, constraints, solution methodologies, practical findings, limitations, and possible extensions of the two studies. Both papers formulate realistic operational decisions using mixed-integer linear programming and employ heuristic or metaheuristic approaches for larger instances. The Chilean study reports transportation-cost reductions of up to 10% from introducing milk collection centres, while the Turkish study demonstrates the computational usefulness of a Variable Neighbourhood Search framework for realistic constrained instances. The comparison shows how the classical transportation model can be extended through facility location, routing, capacity, incompatibility, loading, and time-window constraints to represent real dairy logistics. The analysis also identifies uncertainty, seasonality, spoilage risk, and data requirements as areas for further model development.

Keywords: Operations Research; Milk Collection; Transportation Problem; Vehicle Routing; Mixed-Integer Linear Programming; Logistics