A Layered Mixed Integer Linear Programming Approach for Truck Appointment System Design in Port Automation Application

This paper describes the development of a truck appointment system (TAS) algorithm in a port that mainly handles bulk cargo ships. The developed TAS algorithm is based on a two-stage mixed-integer linear programming (MILP) scheme. The first stage of the proposed scheme essentially formulates and solves a MILP problem to determine the number of trucks required by each consignee of the ship to handle/transport its part of the ship cargo. Based on the obtained number of trucks, the second stage of the scheme then formulates and solves the second MILP problem to schedule the arrival times and sequence of these trucks at the port subject to the operational parameters and characteristic of the port. Simulation results are reported to illustrate the effectiveness of the proposed TAS algorithm to optimize port operations.

Authors

Institutions

Publication Details

Published
2025-08-20
DOI
https://doi.org/10.1109/icevt67191.2025.11183934
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Layered Mixed Integer Linear Programming Approach for Truck Appointment System Design in Port Automation Application

Tua A. Tamba
Advanced Manufacturing and Logistics Optimization
article

A Layered Mixed Integer Linear Programming Approach for Truck Appointment System Design in Port Automation Application

Tua A. Tamba
article en

Abstract

This paper describes the development of a truck appointment system (TAS) algorithm in a port that mainly handles bulk cargo ships. The developed TAS algorithm is based on a two-stage mixed-integer linear programming (MILP) scheme. The first stage of the proposed scheme essentially formulates and solves a MILP problem to determine the number of trucks required by each consignee of the ship to handle/transport its part of the ship cargo. Based on the obtained number of trucks, the second stage of the scheme then formulates and solves the second MILP problem to schedule the arrival times and sequence of these trucks at the port subject to the operational parameters and characteristic of the port. Simulation results are reported to illustrate the effectiveness of the proposed TAS algorithm to optimize port operations.

Parahyangan Catholic University (ID)
Openalex Percentile: Top 61%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.