Optimizing warehouse space allocation to maximize profit in the postal industry
研究了一个基于有界背包问题的模型，帮助邮政公司选择高利润客户并分配仓储空间，以最大化利润，并通过启发式方法提升整体盈利能力。
This study develops a model to optimize warehouse space allocation to maximize throughput based on the capabilities of the delivery company. A bounded knapsack model is suggested for strategic customer selection. It integrates the customer’s inputs and the delivery company’s capabilities to determine a subset of customers and the respective volume amounts that need to be selected from each customer to maximize the company’s profit. The aim is to enhance profit by choosing customers with high profitability, considering penalties, and ensuring the total processed volume does not exceed the facility’s capacity. A heuristic method is suggested and tested. This method enables postal organizations to leverage their current assets and procedures to gain an edge in the expanding e-commerce sector. Numerical analyses indicate that the proposed greedy heuristic results in penalty values that are comparable to or lower than those of traditional methods, and it enhances the overall profitability of the postal organization. • Process of customer selection for postal industry utilizing profits and penalties. • Problem formulation modeled after the bounded knapsack problem. • Optimizing warehouse space utilization to maximize profits. • Greedy heuristic approach introduced for simple analysis. • Applicable in fulfillment, 3PL, last mile delivery industry.