Abstract
In the field of logistics, efficient scheduling and resource allocation are essential for ensuring the seamless flow of goods through transportation networks. This paper addresses the Interval Scheduling Problem, a combinatorial optimization challenge, in the context of logistics planning for goods transportation. The study examines how optimized appointment scheduling and resource allocation can enhance the performance of transportation networks. By combining theoretical insights, algorithmic solutions, and practical applications, this work proposes a comprehensive approach grounded in mathematical models that account for time, resource, and capacity constraints, alongside a computational implementation. Utilizing advanced computational techniques and real-time data integration, the proposed solutions aim to increase operational effectiveness and competitiveness while reducing costs in transportation logistics.