A Hybrid Method for Assigning Containers to AGVs in Container Terminal

Zaghdoud, Radhia; Mesghouni, Khaled; Dutilleul, Simon Collart; Zidi, Kamel; Ghédira, Khaled

doi:10.1016/j.ifacol.2016.07.017

Cited by 21 publications

(12 citation statements)

References 17 publications

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“…Based on the subproblems Bish et al raised, the following researchers had made a further study. Zaghdoud et al [3] proposed a hybrid approach that combined the Dijkstra algorithm, genetic algorithm, and a heuristic method to solve the assignment of containers to AGVs problem. Angeloudis and Bell [4] proposed a flexible dispatching algorithm along with a new AGV dispatching approach for job assignments problems in container terminal settings under various conditions of uncertainty.…”

Section: Related Workmentioning

confidence: 99%

An Improved Shuffled Frog Leaping Algorithm for Multiload AGV Dispatching in Automated Container Terminals

Bian

Gao

2020

Mathematical Problems in Engineering

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Multiload AGVs, which can carry more than one container at a time, are widely used in automated container terminals. The dispatching decisions for multiload AGVs serving in automated container terminals on the target of minimum travel distance are significant in the process of container transportation in terms of improving operating efficiency. Previous work usually focused on AGVs working in a single-carrier mode, which was not only inconsistent with actual circumstances but also a waste of resources. In this paper, we establish a new mathematical model to describe multiload AGVs operating in automated container terminals, which is closer to the actual situation in real terminals. Based on this improved model, we propose a priority rule-based algorithm, termed as shuffled frog leaping algorithm with a mutant process (SFLAMUT), which can increase the diversity of the population and improve the convergence rate. Experiments were carried out based on data generated randomly according to the working properties of container terminals, and it is observed that the proposed SFLAMUT presents an effective and efficient exploration process and yields promising results in solving the proposed mathematical model.

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Section: Related Workmentioning

confidence: 99%

An Improved Shuffled Frog Leaping Algorithm for Multiload AGV Dispatching in Automated Container Terminals

Bian

Gao

2020

Mathematical Problems in Engineering

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“…Xiaoyong Liao, Yang Wang, Jingdong Lin College of Automation, Chongqing University, Chongqing, China Zaghdoud et al [4] mix Dijkstra algorithm, genetic algorithm and heuristic method to settle multi-AGVs path planning of container terminal. Sun et al [5] combine Dijkstra algorithm with dynamic time window algorithm to solve multi-AGVs path planning in parking lot.…”

Section: ________________________________mentioning

confidence: 99%

Multi-AGVs Path Planning in Intelligent Parking Lot

Liao¹,

Yang²,

Lin³

2019

dtcse

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The problem of path planning for multiple Automated Guided vehicles (AGVs) in intelligent parking lot. Proposing a path planning algorithm that combining K shortest path with time window. Firstly, using the visibility graph algorithm to model the parking lot. According to the established model, the K short paths of each AGV are obtained by combining the A star and path deviation algorithm. Then, the time window algorithm is used to predict the time that each AGV occupies path. If some AGVs's time windows have overlapped, comparing the waiting strategy with the alternative K paths strategy, and the shortest strategy is adapted to solve the conflict. Finally, an example is given to verify the proposed algorithm, and the results show that the proposed algorithm can plan a collision-free path for each AGV in the intelligent parking lot of multiple AGVs. And the searching speed is relatively fast.

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“…(2) Research on optimization of automated terminal operation system: recent research on the automated terminal horizontal transportation was mostly concentrated on the scheduling of AGVs [19][20][21][22]. To solve the path conflicts for an AGV that may occur in the horizontal transportation of automated container terminal, a control strategy was proposed by adjusting the AGV speed of the path node location [19].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“…To solve the path conflicts for an AGV that may occur in the horizontal transportation of automated container terminal, a control strategy was proposed by adjusting the AGV speed of the path node location [19]. Zaghdoud et al proposed a method to generate collision-free trajectory of AGVs, which would reduce the completion time of container operation [20]. Xin et al proposed a hierarchical control structure for integrating AGV interactive scheduling and trajectory planning [21].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

The Three-Stage Integrated Optimization of Automated Container Terminal Scheduling Based on Improved Genetic Algorithm

2021

Mathematical Problems in Engineering

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This paper proposes an improved GA (genetic algorithm)-based integrated optimization of automated container terminal scheduling. The three-stage integrated optimization model of automated container terminal scheduling is suggested, and the objective is the minimal operation time of the loading and unloading tasks at the automated container terminal. To solve the difficult combination problem, an improved GA, which is named PGA (Probability Genetic Algorithm), is developed. As traditional GA does not change the probability according to the specific iterations in the population, PGA improves the above limitation to improve population distribution and accelerate convergence. Different from published literature, the study of this paper can be presented in two aspects. One is in the modeling; it includes (i) formalizing the description of the purpose of the model and (ii) having a real-world coordination of three types of equipment that are incorporated at automated container terminals. The other is that PGA is applied to deal with the integrated scheduling whose results can be gotten with better solving speed and convergence. Numerical experiments show that the model constructed in this paper has important reference value for the optimum ratio of QCs, AGVs, and ASCs in automated container operation, which is of great significance to improve the efficiency of the automated terminal. Furthermore, compared with the results of traditional GA and PSO (particle swarm optimization), the speed and convergence of PGA have been greatly improved.

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A Hybrid Method for Assigning Containers to AGVs in Container Terminal

Cited by 21 publications

References 17 publications

An Improved Shuffled Frog Leaping Algorithm for Multiload AGV Dispatching in Automated Container Terminals

An Improved Shuffled Frog Leaping Algorithm for Multiload AGV Dispatching in Automated Container Terminals

Multi-AGVs Path Planning in Intelligent Parking Lot

The Three-Stage Integrated Optimization of Automated Container Terminal Scheduling Based on Improved Genetic Algorithm

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