scholarly journals Connected Automated Guided Vehicles in a Smart Container Terminal

2019 ◽  
Vol 533 ◽  
pp. 012029
Author(s):  
Mohamed K. Watfa ◽  
Khaldon Al Karmadi
Keyword(s):  
Container Terminal ◽  
Automated Guided Vehicles

scholarly journals Research on Cooperative Scheduling of Automated Quayside Cranes and Automatic Guided Vehicles in Automated Container Terminal

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Qianru Zhao ◽  
Shouwen Ji ◽  
Dong Guo ◽  
Xuemin Du ◽  
Hongxuan Wang
Keyword(s):  
Search Algorithm ◽  
Container Terminal ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Total Energy Consumption ◽  
Two Stage ◽  
Taboo Search ◽  
Automatic Guided Vehicles ◽  
Collaborative Scheduling ◽  
Taboo Search Algorithm

According to previous research studies, automated quayside cranes (AQCs) and automated guided vehicles (AGVs) in automated container terminals have a high potential synergy. In this paper, a collaborative scheduling model for AQCs and AGVs is established and the capacity limitation of the transfer platform on AQCs is considered in the model. The minimum total energy consumption of automated quayside cranes (AQCs) and Automatic Guided Vehicles (AGVs) is taken as the objective function. A two-stage taboo search algorithm is adopted to solve the problem of collaborative scheduling optimization. This algorithm integrates AQC scheduling and AGV scheduling. The optimal solution to the model is obtained by feedback from the two-stage taboo search process. Finally, the Qingdao Port is taken as an example of a data experiment. Ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the two-stage taboo search algorithm since it can find near-optimal solutions, precisely and accurately.

scholarly journals Performance Analysis on Transfer Platforms in Frame Bridge Based Automated Container Terminals

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Hongtao Hu ◽  
Byung Kwon Lee ◽  
Youfang Huang ◽  
Loo Hay Lee ◽  
Ek Peng Chew
Keyword(s):  
Markov Chain ◽  
Performance Analysis ◽  
Markov Chain Model ◽  
Container Terminal ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Chain Model ◽  
Quay Cranes ◽  
Automated Container Terminal ◽  
Multistory Frame

This paper studies a new automated container terminal (ACT) system which utilizes multistory frame bridges and rail-mounted trolleys to transport containers between the quay and the yard. Beside typical ACT systems use trucks or automated guided vehicles for transporting containers between quay cranes and yard cranes, the new design uses three types of handling machines, namely, ground trolleys (GTs), transfer platforms (TPs), and frame trolleys (FTs). These three types of handling machines collaborate with one another to transport containers. This study decomposes the system into several subsystems. Each subsystem has one TP and several FTs and GTs dedicated to this TP. Then, a Markov chain model is developed to analyze the throughput of TPs. At last, the performance of the new ACT system is estimated. Sensitivity analyzes the numbers, and the processing rates of trolleys are conducted through the numeric experiments.

scholarly journals Modeling and Design of Container Terminal Operations

2020 ◽  
Vol 68 (3) ◽  
pp. 686-715 ◽  
Author(s):  
Debjit Roy ◽  
René De Koster ◽  
René Bekker
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Heavy Traffic ◽  
Building Blocks ◽  
Transport Processes ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Design Parameters ◽  
Container Terminal Operations ◽  
Terminal Operations

The design of container terminal operations is complex because multiple factors affect operational performance. These factors include numerous choices for handling technology, terminal topology, and design parameters and stochastic interactions between the quayside, stackside, and vehicle transport processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with automated lift vehicles and automated guided vehicles. These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of different vehicle dwell point policies and efficient terminal layouts are analyzed. We show the relation among the dwell point–dependent waiting times and also show their asymptotic equivalence at heavy traffic conditions. These models form the building blocks for design and analysis of large-scale terminal operations. We test the model efficacy using detailed simulation experiments and real-terminal validation.

Dispatching Automated Guided Vehicles in a Container Terminal

2005 ◽  
pp. 355-389 ◽  
Author(s):  
Yong-Leong Cheng ◽  
Hock-Chan Sen ◽  
Karthik Natarajan ◽  
Chung-Piaw Teo ◽  
Kok-Choon Tan
Keyword(s):  
Container Terminal ◽  
Automated Guided Vehicles

scholarly journals Adaptive Autotuning Mathematical Approaches for Integrated Optimization of Automated Container Terminal

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Meisu Zhong ◽  
Yongsheng Yang ◽  
Yamin Zhou ◽  
Octavian Postolache
Keyword(s):  
Programming Model ◽  
Container Terminal ◽  
Operation Mode ◽  
Pso Algorithm ◽  
Container Terminals ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Integrated Scheduling ◽  
Loading And Unloading ◽  
Unloading Time

With the development of automated container terminals (ACTs), reducing the loading and unloading time of operation and improving the working efficiency and service level have become the key point. Taking into account the actual operation mode of loading and unloading in ACTs, a mixed integer programming model is adopted in this study to minimize the loading and unloading time of ships, which can optimize the integrated scheduling of the gantry cranes (QCs), automated guided vehicles (AGVs), and automated rail-mounted gantries (ARMGs) in automated terminals. Various basic metaheuristic and improved hybrid algorithms were developed to optimize the model, proving the effectiveness of the model to obtain an optimized scheduling scheme by numerical experiments and comparing the different performances of algorithms. The results show that the hybrid GA-PSO algorithm with adaptive autotuning approaches by fuzzy control is superior to other algorithms in terms of solution time and quality, which can effectively solve the problem of integrated scheduling of automated container terminals to improve efficiency.

scholarly journals Flexibility management and provision of balancing services with battery-electric automated guided vehicles in the Hamburg container terminal Altenwerder

2020 ◽  
Vol 3 (S1) ◽  
Author(s):  
Stefanie Holly ◽  
Astrid Nieße ◽  
Martin Tröschel ◽  
Lasse Hammer ◽  
Christoph Franzius ◽  
...  
Keyword(s):  
Container Terminal ◽  
Automated Guided Vehicles ◽  
Use Case ◽  
Multi Agent System ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Multi Agent ◽  
And Control ◽  
Balancing Services ◽  
High Uncertainty

Abstract Unlocking and managing flexibility is an important contribution to the integration of renewable energy and an efficient and resilient operation of the power system. In this paper, we discuss how the potential of a fleet of battery-electric transportation vehicles can be used to provide frequency containment reserve. To this end, we first examine the use case in detail and then present the system designed to meet this challenge. We give an overview of the tasks and individual sub-components, consisting of (a) an artificial neural network to predict the availability of Automated Guided Vehicles (AGVs) day-ahead, (b) a heuristic approach to compute marketable flexibility, (c) a simulation to check the plausibility of flexibility schedules, (d) a multi-agent system to continuously monitor and control the AGVs and (e) the integration of fleet flexibility into a virtual power plant. We also present our approach to the economic analysis of this provision of a system-critical service in a logistical context characterised by high uncertainty and variability.

scholarly journals An Optimization Model of Integrated AGVs Scheduling and Container Storage Problems for Automated Container Terminal Considering Uncertainty

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1904
Author(s):  
Wentao Jian ◽  
Jishuang Zhu ◽  
Qingcheng Zeng
Keyword(s):  
Optimization Model ◽  
Container Terminal ◽  
Operation Time ◽  
Triangular Fuzzy Number ◽  
Automated Guided Vehicles ◽  
Improved Genetic Algorithm ◽  
Running Time ◽  
Location Allocation ◽  
Storage Location ◽  
Maximum Completion Time

The running path of automated guided vehicles (AGVs) in the automated terminal is affected by the storage location of containers and the running time caused by congestion, deadlock and other problems during the driving process is uncertain. In this paper, considering the different AGVs congestion conditions along the path, a symmetric triangular fuzzy number is used to describe the AGVs operation time distribution and a multi-objective scheduling optimization model is established to minimize the risk of quay cranes (QCs) delay and the shortest AGVs operation time. An improved genetic algorithm was designed to verify the effectiveness of the model and algorithm by comparing the results of the AGVs scheduling and container storage optimization model based on fixed congestion coefficient under different example sizes. The results show that considering the AGVs task allocation and container storage location allocation optimization scheme with uncertain running time can reduce the delay risk of QCs, reduce the maximum completion time and have important significance for improving the loading and unloading efficiency of the automated terminal.

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