An optimization approach for wharf location by Genetic algorithm, event tree and neural network; Case study: mechanized railway terminal for transportation of mineral bulk materials in Shahid Rajaei port

Jafari, Hamed; Shirzadi Javid, Ali Akbar; Ghoddousi, Parviz; Malekitabar, Hassan; Naderi, Mohsen

doi:10.22065/jsce.2024.446325.3367

An optimization approach for wharf location by Genetic algorithm, event tree and neural network; Case study: mechanized railway terminal for transportation of mineral bulk materials in Shahid Rajaei port

Document Type : Original Article

Authors

Hamed Jafari ¹

Ali Akbar Shirzadi Javid ²

parviz ghoddousi ³

Hassan Malekitabar ⁴

Mohsen Naderi ⁵

¹ Master of science student, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

² Associate Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

³ Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

⁴ Assistant Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

⁵ Master of science, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran

10.22065/jsce.2024.446325.3367

Abstract

In this research, by using the genetic algorithm, which is a type of meta heuristic algorithms, the optimal number of wharfs is calculated based on the number of existing ships, the profit from the export and import of iron ore, and the waiting time. The best chromosome of each generation is classified according to the maximum amount of profit obtained during the operation period of the project. In addition to identifying the best number of ships and waiting time, it also identifies the best possible capacity for the project by using the event tree and taking into account the possibilities of tides, market supply and demand, and the impact of the sanction, so that the project can reach to the maximum profit at the time of operation with the least risk. Then, by using the neural network and taking into account the costs of dredging, dike and conveyor belt, the exact location of the dike is determined, so that the cost of construction is reduced to the minimum possible amount.

This research has been carried out as a case study on the construction of a mechanized rail terminal for mineral bulk materials in Shahid Rajaei port and it helps the experts in this field for feasibility and basic studies to identify the most optimal mode as soon as possible in order to Avoid wasting time and resources. In this research, the use of 2 wharfs with a capacity of 16 million tons per year has been identified as the best plan. Also; The best place to build a wharf has been identified at a distance of 350 meters from the end of the land.

Keywords

genetic algorithm

mechanized rail terminal for mineral bulk materials of Shahid Rajaei port

optimal location of the wharf

optimal number of wharfs

neural network

Subjects

Project and Construction Management

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