Flow Path Design for Automated Transport Systems in Container Terminals Considering Traffic Congestion

Singgih, Ivan Kristianto; Hong, Soondo; Kim, Kap Hwan

doi:10.7232/iems.2016.15.1.019

Cited by 11 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The time window is determined in constraints (14) and (15) by each QC according to the first phase results. Constraints (16) and (17) ensure that each container is served by quay crane under the time windows. The actual handling time of the nth container by quay crane is determined in constraints (18) and (19).…”

Section: Phase Ii: Mathematical Formulation For Agv Schedulingmentioning

confidence: 99%

“…Some researchers have addressed the impact of the uncertain environment of AGV transportation. For example, Singgih [17] studied the AGV path planning problem of automated container terminals with consideration of congestion. An integer programming model was constructed with the objective of minimizing the transiting time and waiting time of the AGV and solved it using the Dijkstra algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability

2019

View full text Add to dashboard Cite

This study proposes a formulation to optimize operational efficiency of a dual-trolley quay crane and automatic guided vehicles (AGVs) to reduce energy consumption at an automated container terminal. A two-phase model is used to minimize energy consumption during loading and discharging operations, as well as maximize the utilization rate of the AGVs, with consideration of relevant constraints such as the capacity of buffers for the quay crane (QC) and yard, the stability of vessel, the maximum endurance of an AGV, and the available laytime for handling. We propose a constrained partial enumeration strategy to construct quay crane schedules and a genetic algorithm to solve the AGV scheduling problem. Finally, Yangshan Phase IV automated container terminal's data is used to verify the validity and applicability of the proposed model. The results of the tests provide evidence that the proposed method can improve energy efficiency.

show abstract

Section: Phase Ii: Mathematical Formulation For Agv Schedulingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability

2019

View full text Add to dashboard Cite

show abstract

“…Guan et al [8] proposed an improved electromagnetism-like mechanism algorithm to minimize both loaded and empty travel distance. Functionally similar approaches also include the genetic algorithm [9,10] and the met heuristics algorithm [11].…”

Section: Introductionmentioning

confidence: 99%

“…Example of UGN mutation operation 10. Mathematical Problems in EngineeringThe i-th generation population G i p2Candidate populationThe (i + 1) -th generation population G p2…”

mentioning

confidence: 99%

A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

Xiao

Zeng

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

In the current industrial fields, automatic guided vehicles (AGVs) are widely employed to constitute the flexible manufacturing system (FMS), owing to their great advantages of routing flexibility and high efficiency. However, one main challenge lies in the coupling process of the design problem of the unidirectional guide-path network (UGN) and the task scheduling problem of AGVs. To reduce the complexity, most pertinent literatures only handle these problems one by one, based on the stepwise design methods, thereby neglecting the constraint conditions and the optimization objectives caused by the FMS environment. The motivation of the paper is to bring the coupling factors into the integrated design and solution process. Firstly, an integrated design model of designing UGN and scheduling AGVs simultaneously is proposed, with the objective of minimizing the makespan (i.e., the maximum completion time of all handling tasks), in the consideration of the practical constraints, e.g., the job handling and processing sequence constraints and the AGV number constraint. Secondly, a dual-population collaborative evolutionary genetic algorithm (CEGA) is developed to solve the problems of designing and scheduling in a parallel way. The solutions of the integrated model, i.e., the potential strongly connected UGN and the feasible processing and handling sequence, are, respectively, coded as two different subpopulations with independent and concurrent evolution processes. The neighbourhood search operation, the niche technique, and the elitism strategy are combined to improve the convergence speed and maintain the population diversity. The experimental results show that the integrated design model can formulate the problem more accurately, and the CEGA algorithm is computationally efficient with high solution quality.

show abstract

“…Increased trade volume carried by container ships has motivated container terminal operators and engineers to develop more sophisticated strategies and container terminal designs [2][3][4][5] for improving throughput and storage capacity [6][7][8]. One design concept is the rail-based automated container terminal (RACT) [8], which comprises a quay area, a transport area, and a storage yard area. Figure 1 (a) and (b) shows the infrastructure of the RACT.…”

Section: Introductionmentioning

confidence: 99%

A Job Sequencing Problem of an Overhead Shuttle Crane in a Rail-Based Automated Container Terminal

Fibrianto¹,

Kang

Hong

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

This study proposes a job scheduling model and its heuristics for an automated container terminal with an overhead shuttle crane (OS) to reduce the total tardiness time of flatcars and external trucks by considering the separation of each job into a main job, and a premarshaling or remarshaling job. The OS is busy or idle according to the fluctuations in the processing times of different pieces of equipment. We identify the OS job sequencing problem considering job separation (OSJSPS) as a mixed-integer programming (MIP) model, which simultaneously sequences a set of jobs and searches for their possible separation into premarshaling and remarshaling jobs. We present a two-stage genetic algorithm (TGA) based on two local improvement procedures: an iterative local search procedure and an opportunistic job separation procedure. We conclude that the two-stage genetic algorithm reduces the total tardiness time of the container terminal's flatcars and external trucks as the number of OS jobs increases.

show abstract

Flow Path Design for Automated Transport Systems in Container Terminals Considering Traffic Congestion

Cited by 11 publications

References 22 publications

Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability

Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability

A CEGA-Based Optimization Approach for Integrated Designing of a Unidirectional Guide-Path Network and Scheduling of AGVs

A Job Sequencing Problem of an Overhead Shuttle Crane in a Rail-Based Automated Container Terminal

Contact Info

Product

Resources

About