Improving truck service performance in transporting rock aggregate using Genetic Ant Colony Algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.314147

Keywords:

service performance, transportation, rock aggregate, terminal for their own needs

Abstract

Inter-island shipment requests for rock aggregate products are served through the terminal for their own needs (TFON). The high demand for rock aggregate products causes many ships to queue up to be loaded. However, this condition is not comparable to the availability of dump trucks used to serve loading and unloading activities. This study aims to improve the performance of dump truck service in transporting rock aggregate so that the number of dump truck vehicles and optimal loading and unloading service times from the stockpile to ship at TFON are obtained. The research location was carried out at active rock mining companies in the Central Sulawesi region. The data collection method is carried out using field surveys (observations) using a time recording device by recording the process of transporting rock aggregates from the stockpile location to the ship in TFON and collecting secondary data on the demand for rock aggregates to be transported. The analysis method uses the hybrid Genetic Ant Colony Algorithm (ACO-GA) method namely a combination method between the Ant Colony Optimization algorithm and the Genetic Algorithm which aims to maximize the optimal number of trucks used in the transportation process and minimize the time in the loading and unloading process. The results showed that there had been an increase in service performance of the dump truck used in transporting rock aggregate with the longest distance of 2.3 km with a total of 5 dump trucks. The number of dump trucks of 5 units was selected because it falls within the fitness value criteria which is closest to the optimum value or equal to the value of the resources owned. Meanwhile, the optimal loading and unloading process time is in the range of 1.81–3.34 working days

Supporting Agency

  • Expressions of thanks are expressed to the management of terminals for their own needs (TFON) who have provided a lot of data and information support in this research activity.

Author Biographies

Syarifuddin Ishak, Brawijaya University

Doctoral Student of Civil Engineering

Department of Civil Engineering

Ludfi Djakfar, Brawijaya University

Professor

Department of Civil Engineering

Achmad Wicaksono, Brawijaya University

Philosophy of Doctor, Associate Professor

Department of Civil Engineering

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Improving truck service performance in transporting rock aggregate using Genetic Ant Colony Algorithm

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Published

2024-10-30

How to Cite

Ishak, S., Djakfar, L., & Wicaksono, A. (2024). Improving truck service performance in transporting rock aggregate using Genetic Ant Colony Algorithm. Eastern-European Journal of Enterprise Technologies, 5(3 (131), 82–90. https://doi.org/10.15587/1729-4061.2024.314147

Issue

Vol. 5 No. 3 (131) (2024): Control processes

Section

Control processes

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Copyright (c) 2024 Syarifuddin Ishak, Ludfi Djakfar, Achmad Wicaksono

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