South Africa faces a critical shortage of blood donors, leading to substantial deficits in the national blood supply. Blood donations are vital for treating life-threatening conditions, making it crucial to develop efficient models for managing blood stocks. This paper presents a mathematical model to optimize blood donation and ensure sufficient supply to meet fluctuating demands. The model captures the complex interactions within the blood banking system, focusing on minimizing costs, reducing waste, and efficiently distributing blood units. Specifically, it addresses daily supply challenges by minimizing the need for emergency imports and reducing blood wastage due to expiration while meeting all demand requirements. The core objective is to minimize blood wastage and reduce the reliance on imported blood banks during emergencies. The proposed objective function incorporates variables such as emergency importation and expiration rates, and robust optimization techniques are applied to identify optimal solutions while satisfying operational constraints. Symbiotic Organism Search (SOS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) methods are utilized for optimization. Among these, SOS demonstrated superior performance, achieving the lowest levels of importation and wastage. However, the algorithms could not significantly reduce supply levels due to the accumulation of excess stock from the previous day, which carried over into the next day. This paper provides valuable information on blood supply management and highlights the potential for optimization techniques to improve efficiency and sustainability in blood banking.