A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals

Rashidi, Hassan; Tsang, Edward

doi:10.1016/j.camwa.2010.12.009

Cited by 54 publications

(28 citation statements)

References 9 publications

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“…Lee et al [5] consider the problem with the quay cranes and yard cranes capacity. Rashidi et al [6], solve the problem by a novel algorithm, NSA+, which extended the standard Network Simplex Algorithm (NSA). Moussi et al [7], develop a heuristic for the dispatching problem of automated lifting vehicles (ALV) which can lift containers from the ground by themselves.…”

Section: Problem Statementmentioning

confidence: 99%

Study on Shuttle Scheduling Problem in Automated Container Terminal

Shen¹,

Zhao²,

Mi³

et al. 2014

TOAUTOCJ

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Abstract:Owing to the shuttle in Mixed Operation Mode of Shuttle-based automated container terminal handles loading, unloading, congregation and delivery operations .simultaneously, conventional scheduling method cannot be applied. Accordingly, this paper proposed a mathematical scheduling model. The objective is to minimize shuttle operation time and deal with loading and unloading with priority while avoiding unbearable waiting time for congregation and delivery tasks. Due to the complexity of this model, a Genetic Algorithm (GA) is designed for effective solutions. Numerical experiment is conducted to examine the key factors of the problem and the performance of the proposed GA.

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Section: Problem Statementmentioning

confidence: 99%

Study on Shuttle Scheduling Problem in Automated Container Terminal

Shen¹,

Zhao²,

Mi³

et al. 2014

TOAUTOCJ

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“…For example, a complete algorithm based on extended network simplex algorithm has been proposed for AGV scheduling with single objective (i.e., flow cost) considered, which cannot obtain the optimal schedule if it cannot find one within the time available [22]. As a complement, an incomplete algorithm based on greedy vehicle search has also been developed in [22], which is an approximate approach. A multilayer genetic algorithm and a genetic algorithm plus maximum matching have been developed for the AGV scheduling integrated with other yard equipment and using the AGV traveling time as one objective, which can only obtain the near-optimal solution [23].…”

Section: Introductionmentioning

confidence: 98%

“…The main difference is that SCs can pickup and setdown containers without the need of yard cranes, thus the scheduling problem is more independent. Different models, methods and rules have been developed for the AGV scheduling (or termed task assignment) [2], [22], [23]. For example, a complete algorithm based on extended network simplex algorithm has been proposed for AGV scheduling with single objective (i.e., flow cost) considered, which cannot obtain the optimal schedule if it cannot find one within the time available [22].…”

Section: Introductionmentioning

confidence: 99%

“…Different models, methods and rules have been developed for the AGV scheduling (or termed task assignment) [2], [22], [23]. For example, a complete algorithm based on extended network simplex algorithm has been proposed for AGV scheduling with single objective (i.e., flow cost) considered, which cannot obtain the optimal schedule if it cannot find one within the time available [22]. As a complement, an incomplete algorithm based on greedy vehicle search has also been developed in [22], which is an approximate approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiobjective Optimization for Autonomous Straddle Carrier Scheduling at Automated Container Terminals

Cai

Huang

Liu

et al. 2013

IEEE Trans. Automat. Sci. Eng.

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A multiobjective optimization model is presented in this paper for the Autonomous Straddle Carriers Scheduling (ASCS) problem in automated container terminals, which is more practical than the single objective model. The model considers three objectives [i.e., Straddle Carriers (SCs) traveling time, SC waiting time and finishing time of high-priority container-transferring jobs], and their weighted sum is investigated as the representative example. The presented model is formulated as a pickup and delivery problem with time windows in the form of binary integer programming. An exact algorithm based on Branch-and-Bound with Column Generation (BBCG) is employed for solving the multiobjective ASCS problem. Based on the map of an actual fully automated container terminal, simulation results are compared with the single-objective scheduling to demonstrate the effectiveness and flexibility of the presented multiobjective model, as well as the efficacy of the BBCG algorithm for autonomous SC scheduling.Note to Practitioners-Effective operation of straddle carriers is very important for container terminal managers to increase the productivity and reduce the operational cost of container transportation at automated terminals. This study develops a multiobjective model and an exact algorithm for the task allocation of container transportation using autonomous straddle carriers. Based on different optimization requirements, the optimal schedule and cost obtained by the presented multiobjective model and the exact algorithm can help the terminal operators to evaluate the performance of the operation of straddle carriers in terms of container transportation. The study can also provide an effective and flexible operational scheme for terminal managers.

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“…On the one hand, practical applications inspired intensive studies on flexible manufacturing systems within operational research, which resulted in numerous papers on specific problems [3][4][5][6][7][8][9], including robotic cells problems [10,11] and surveys of results [12][13][14][15][16]. On the other hand, closely related problems, concerning automated guided vehicles traffic control systems, could be found in logistics, e.g., in automated container terminals [17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Complexity of Scheduling Problem in Single-Machine Flexible Manufacturing System with Cyclic Transportation and Unlimited Buffers

Espinouse

Pawlak

Sterna

2017

J Optim Theory Appl

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The paper concerns complexity studies on the scheduling problem arising in a simple flexible manufacturing system. The system consists of a single machine, one depot (both with unlimited buffers), and one vehicle (automated guided vehicle). The vehicle operates according to the regular metro strategy. This means that it travels in cycles of the constant length, without stops, transporting at most one job at a time between the depot and the machine. The machine executes available jobs in the nonpreemptive way. The goal is to minimize the schedule length, i.e., to minimize the number of vehicle cycles necessary to transport and execute all jobs in the system. We prove the strong NP-hardness of this problem and show that any list algorithm has the worst-case performance ratio equal to 2. Moreover, we mention that special cases of the considered problem, with zero transportation times from the depot to the machine and from the machine to the depot, are polynomially solvable.

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A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals

Cited by 54 publications

References 9 publications

Study on Shuttle Scheduling Problem in Automated Container Terminal

Study on Shuttle Scheduling Problem in Automated Container Terminal

Multiobjective Optimization for Autonomous Straddle Carrier Scheduling at Automated Container Terminals

Complexity of Scheduling Problem in Single-Machine Flexible Manufacturing System with Cyclic Transportation and Unlimited Buffers

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