TY - GEN
T1 - Analyzing Freight Truck Arrival Scheduling and Operations for an International Beverage Company’s Warehouse
AU - Muñoz-Villamizar, Andres
AU - Montoya-Torres, Jairo
AU - Mejía-Argueta, Christopher
AU - Queirolo, Julian
AU - Hernandez, Daniel
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - This study examines delays in processing returned shipments at a beverage distribution center in Bogotá, Colombia. Returned trucks undergo reception, inspection, and reloading processes, which can result in congestion at the processing docks. We develop a discrete-event simulation model based on historical operational data and a focused time-and-motion study to represent the current system. Two improvement scenarios are evaluated: (1) increased verification staffing, and (2) regulated truck arrivals (i.e., arrival scheduling). Performance is assessed in terms of average turnaround time, average waiting time, processing time, queue length, resource utilization, and number of external waiting vehicles (i.e., congestion caused around the distribution center to citizens). Simulation results indicate that the addition of staff reduces truck turnaround by approximately 30%, decreases the average queue length by over 60%, and lowers peak dock utilization. Meanwhile, managed arrivals yield more consistent throughput, with a 20% reduction in waiting times and decreased variability in resource use. Both interventions enhance driver work–life balance, improve service levels, and mitigate community impacts caused by external queuing. The proposed framework offers a replicable, data-driven approach for distribution centers to mitigate dock-level bottlenecks, enabling informed decision-making on resource allocation and scheduling strategies.
AB - This study examines delays in processing returned shipments at a beverage distribution center in Bogotá, Colombia. Returned trucks undergo reception, inspection, and reloading processes, which can result in congestion at the processing docks. We develop a discrete-event simulation model based on historical operational data and a focused time-and-motion study to represent the current system. Two improvement scenarios are evaluated: (1) increased verification staffing, and (2) regulated truck arrivals (i.e., arrival scheduling). Performance is assessed in terms of average turnaround time, average waiting time, processing time, queue length, resource utilization, and number of external waiting vehicles (i.e., congestion caused around the distribution center to citizens). Simulation results indicate that the addition of staff reduces truck turnaround by approximately 30%, decreases the average queue length by over 60%, and lowers peak dock utilization. Meanwhile, managed arrivals yield more consistent throughput, with a 20% reduction in waiting times and decreased variability in resource use. Both interventions enhance driver work–life balance, improve service levels, and mitigate community impacts caused by external queuing. The proposed framework offers a replicable, data-driven approach for distribution centers to mitigate dock-level bottlenecks, enabling informed decision-making on resource allocation and scheduling strategies.
KW - Discrete Event Simulation
KW - Reverse Logistics
KW - Unloading
KW - Warehouse Receiving Process
UR - https://www.scopus.com/pages/publications/105029736623
U2 - 10.1007/978-3-032-15579-5_11
DO - 10.1007/978-3-032-15579-5_11
M3 - Contribution to conference proceedings
AN - SCOPUS:105029736623
SN - 9783032155788
T3 - Communications in Computer and Information Science
SP - 169
EP - 182
BT - Innovative Intelligent Industrial Production and Logistics - 6th IFAC/INSTICC International Conference, IN4PL 2025, Proceedings
A2 - Barata, José
A2 - Madani, Kurosh
A2 - Panetto, Hervé
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2025
Y2 - 23 October 2025 through 24 October 2025
ER -