Journals / Celal Bayar Üniversitesi Fen Bilimleri Dergisi / 2016 / Cilt: 12 - Sayı: 1

Container Traffic Prediction in a Seaport Stockyard Implementing Artificial Bee Colony Algorithm Compared with the Genetic Algorithm

Pages
49–54
Publication Date
2022-10-12
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The model results showed that, artificial bee colony algorithm successfully predicted the model coefficients even better than genetic algorithm.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:After finishing the construction stage of a container terminal, it is very difficult to modify the current port configuration and properties.
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Key Findings & Data:For this instance, to avoid of the sunk costs, it is crucial for the seaport designers to predict the container traffic at any stage of the design phase.
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Conclusion & Impact:The model results showed that, artificial bee colony algorithm successfully predicted the model coefficients even better than genetic algorithm.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

After finishing the construction stage of a container terminal, it is very difficult to modify the current port configuration and properties. For this instance, to avoid of the sunk costs, it is crucial for the seaport designers to predict the container traffic at any stage of the design phase. One of the important facilities of a seaport is the container stockyard in which the containers are held for handling operations. The preliminary design of this facility directly influenced by the container traffic and the probable container amount at the stock area. Hence, the required size of the stock area is determined and the further construction costs are directly related with this design parameter. This study proposed a forecasting model for obtaining the daily value of the containers in the stockyard. The proposed model is a simple regressed model with the past records of container traffic in the storage area. The model results showed that, artificial bee colony algorithm successfully predicted the model coefficients even better than genetic algorithm. The results indicated that the model performance is sufficient for predicting the contain amount in a seaport considering the observed records.

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Cite This Article

YILDIRIM, M. S., GÖKKUŞ, Ü., AKOĞLU, K. (2022). Container Traffic Prediction in a Seaport Stockyard Implementing Artificial Bee Colony Algorithm Compared with the Genetic Algorithm. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, Cilt: 12 - Sayı: 1, 49–54. https://ajindex.com/articles/472438

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