Port Container Terminal Quay Crane Allocation Based on Simulation and Machine Learning Method

Indranath Chatterjee,Gyusung Cho

doi:10.18494/sam3645

Abstract

Port Container Terminal Quay Crane Allocation Based on Simulation and Machine Learning Method

Highlights

IntroductionFirst-generation ports centered on cargo handling have developed into second- and thirdgeneration ports, which were the basis for logistics and trade activities, and into fourthgeneration ports where various information provisions and automated loading and unloading have been realized.[1,2] As ports continue to develop, the efficient operation of container terminals is becoming increasingly important.[3,4] To increase the operational efficiency of container terminals, a performance estimation has recently been conducted using simulation methods.[5]
First-generation ports centered on cargo handling have developed into second- and thirdgeneration ports, which were the basis for logistics and trade activities, and into fourthgeneration ports where various information provisions and automated loading and unloading have been realized.[1,2] As ports continue to develop, the efficient operation of container terminals is becoming increasingly important.[3,4] To increase the operational efficiency of container terminals, a performance estimation has recently been conducted using simulation methods.[5]. In particular, in the analysis of container terminal operations, the proper arrangement of the quay crane (QC) is essential because the operational efficiency of the container terminal is improved according to the crane arrangement and operation when used in the quantitative
We focus on the allocation of QCs used in container terminals

Summary

Introduction

First-generation ports centered on cargo handling have developed into second- and thirdgeneration ports, which were the basis for logistics and trade activities, and into fourthgeneration ports where various information provisions and automated loading and unloading have been realized.[1,2] As ports continue to develop, the efficient operation of container terminals is becoming increasingly important.[3,4] To increase the operational efficiency of container terminals, a performance estimation has recently been conducted using simulation methods.[5]. Loading and unloading of containers.[6] as one of the methods for improving the performance of container cranes, we focus on the assignment of quay wall cranes in container terminals based on a simulation in this study. A simulation is the best tool for analyzing nontrivial and real-world systems.[7,8] Simulation methods have become an essential tool for improving terminal operation and performance. The simulation framework is based on a container terminal company located in Busan, Korea.[9,10] We analyze and suggest operations for improving the container productivity for assigning QCs using a simulation method. A summary of commonly utilized metaheuristic approaches for solving the quay allocation problem is provided in this study. We briefly discuss the possibilities of sensor-based IoT techniques in the problem of port management

Container Terminal Operation

ML and Metaheuristic Approaches Involving Quay Allocation

Computational Data Analysis

Integrated aspect-oriented modeling approach

Findings

Conclusions