Transportation planning is a central operations research problem because organizations must allocate limited supply across multiple destinations while controlling the cost of movement. This paper reviews the role of classical transportation models and initial basic feasible solution methods in distribution cost minimization, with particular attention to the Northwest Corner Method (NWC), Least Cost Method (LCM), Row Minima Method (RMM), and Vogel's Approximation Method (VAM). A focused review of selected peer-reviewed literature is combined with a case study of MAISANGO Cement Nigeria Plc. The studies considered here indicate that transportation problems have developed from classical deterministic allocation models toward broader logistics and supply-chain formulations that incorporate multiple objectives, uncertainty, larger networks, and more advanced computational approaches. Within the classical methods, the literature consistently treats NWC, LCM and VAM as procedures for generating an initial basic feasible solution, rather than as guaranteed optimality methods. The MAISANGO case provides a concrete comparison: all four methods ultimately reach the reported optimal transportation cost of NGN 145,140, while their initial solutions and reported iteration requirements differ substantially. VAM begins at NGN 145,380 and reaches the reported optimum in two iterations. The case therefore shows why these classical methods remain useful, both for understanding transportation models and for handling relatively straightforward distribution decisions and their limitations when real distribution systems become dynamic, uncertain, capacity-constrained, or multi-objective. The paper concludes by identifying directions for extending classical transportation models toward more realistic logistics decision-making.