USULAN STRATEGI PENGAMBILAN PETI KEMAS UNTUK MEMINIMASI WAKTU TUNGGU TRUK DI TERMINAL PETI KEMAS (TPK) KOJA MENGGUNAKAN SIMULASI BERBASIS AGEN
Koja Container Terminal (KCT) is one of the container terminals at Tanjung Priok Port, responsible for handling container loading and unloading activities. In 2023, the average turnaround time for imported external trucks at KCT reached 98.94 minutes. The high turnaround time is primarily due to...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/83642 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Koja Container Terminal (KCT) is one of the container terminals at Tanjung Priok
Port, responsible for handling container loading and unloading activities. In 2023,
the average turnaround time for imported external trucks at KCT reached 98.94
minutes. The high turnaround time is primarily due to prolonged truck waiting
times, accounting for 92% of the total turnaround time. KCT plans to implement a
truck reservation system, but currently lacks synchronization between truck
arrivals and container locations, necessitating Rubber-Tyred Gantry (RTG)
reshuffling activities. Reshuffling involves moving containers within a stack slot to
accommodate new arrivals. The current container retrieval strategy employs a
first-come-first-serve approach, causing extensive RTG travel distances and
prolonged handling times. This study aims to propose a container retrieval strategy
and determine the synchronization level for the truck reservation system to be
developed, enabling truck arrivals to synchronize with container locations.
This research employs agent-based simulation methodology. The simulation
models the system by considering interactions among agents. Agent movements are
simulated using discrete event simulation, evaluating each agent at specific events.
In the container retrieval system, the goal for external trucks is to minimize waiting
times, while RTGs aim to minimize inefficiencies. Agent-based simulation
accommodates these individual goals towards a balanced solution, aiming
collectively to minimize average truck waiting times.
Based on the agent-based simulation results, the proposed strategy is a distance-
based container retrieval strategy. Additionally, the addition of a synchronization
module to the truck reservation system is proposed, designed to achieve 100%
synchronization level. The combination of these strategies results in a 31.02%
reduction in truck waiting times in container yard.
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