A new solution approach for the twin yard crane scheduling problem in automated container terminals

The Twin-Automated Stacking Crane (Twin-ASC) system is a special configuration of Yard Crane (YC) that is common in most of the Automated Container Terminals (ACTs) used for stacking and retrieving containers on the yard side of a Container Terminal (CT). The usual objective when scheduling the Twin...

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Vydáno v:Advanced engineering informatics Ročník 57; s. 102015
Hlavní autoři: Oladugba, Andrew Omoniyi, Gheith, Mohamed, Eltawil, Amr
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.08.2023
Témata:
Automated container terminals
Handshake area
Makespan
Solution algorithm
Stacking crane
Stacking crane
Makespan
Handshake area
Solution algorithm
Automated container terminals
ISSN:1474-0346, 1873-5320
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Shrnutí:The Twin-Automated Stacking Crane (Twin-ASC) system is a special configuration of Yard Crane (YC) that is common in most of the Automated Container Terminals (ACTs) used for stacking and retrieving containers on the yard side of a Container Terminal (CT). The usual objective when scheduling the Twin-ASC to perform a given set of transport jobs is the minimization of the schedule length (makespan). The problem is NP-hard, which means that problem of realistic size cannot be solved within a reasonable time limit by default solvers or conventional methods, necessitating the use of an efficient algorithm. Thus, this work proposes a novel algorithm based on the modified Johnson Algorithm (JA) to a formulated Mixed Integer Programming (MIP) model for solving the Twin-ASC scheduling problem to minimize the makespan of the schedule. Differ from the existing heuristics, the proposed algorithm has the flexibility of varying the handshake area, and the system utilization can be investigated. The handshake area is a temporary storage location in the Twin-ASC system where an ASC can leave a job for the other to complete since the crossing of the cranes is not possible, and it greatly affects the makespan of completing the given set of jobs. An extensive computational study was carried out and results were compared with (two) existing heuristics to evaluate the effectiveness of the proposed solution approach.
ISSN:1474-0346
1873-5320
DOI:10.1016/j.aei.2023.102015