Modern supply chains depend heavily on efficient warehouse management since it directly affects operating expenses, space usage, and customer satisfaction. Ineffective or underutilized storage space is frequently the result of poor storage allocation, which drives up costs and delays order processing. The best use of resources cannot be ensured by traditional allocation techniques, which are either manual, or rule based. The paper suggests a Linear Programming (LP) model as a solution to this problem. LP is a popular optimization method that makes it feasible to allocate limited resources effectively while following certain guidelines, leading to the best potential outcome. The methodology created here aims to minimize handling and storage expenses overall while maintaining service-level criteria. Additionally, it guarantees that all of the warehouse's capacity is employed without any unused space. To show how the model works in practice, an example dataset is used. The findings indicate that the Linear Programming-based strategy gives managers a trustworthy decision-support tool for the efficient allocation of goods in a warehouse setting with a constrained capacity