OPTIMIZING TRUCK SCHEDULING AND DOCK ASSIGNMENT THROUGH MIXED-INTEGER LINEAR PROGRAMMING

Abstract

The study presents a Mixed-Integer Linear Programming (MILP) model designed to optimize truck scheduling, dock assignment, and inbound–outbound synchronization in logistics operations. The proposed framework integrates multiple decision variables and constraints to minimize waiting times, reduce operational bottlenecks, and enhance resource utilization at distribution centers. By formulating the problem as a MILP, the model ensures precise allocation of trucks to docks while synchronizing inbound and outbound flows to achieve efficiency in overall supply chain performance. Computational experiments demonstrate the applicability of the model in real-world scenarios, highlighting improvements in turnaround time, cost reduction, and service reliability. The research contributes to logistics optimization by offering a structured mathematical approach that balances operational efficiency with practical feasibility.