A Constrained Programming Model for the Optimization of Industrial-Scale Scheduling Problems in the Shipbuilding Industry
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A Constrained Programming Model for the Optimization of Industrial-Scale Scheduling Problems in the Shipbuilding IndustryDate
2023-07-29Citation
Pernas-Álvarez, J.; Crespo-Pereira, D. A Constrained Programming Model for the Optimization of Industrial-Scale Scheduling Problems in the Shipbuilding Industry. J. Mar. Sci. Eng. 2023, 11, 1517. https://doi.org/10.3390/jmse11081517
Abstract
[Abstract]: This work presents an innovative constrained programming model for solving a flexible
job-shop scheduling problem with assemblies and limited buffer capacity based on a real case from
the shipbuilding industry. Unlike the existing literature, this problem incorporates the manufacturing
and assembly of blocks from subblocks to the final ship erection, while considering the limited buffer
capacity due to the size of blocks, which has been often overlooked. The objectives considered
are the minimization of the makespan and tardiness based on ship erection due dates. To demonstrate
the model’s effectiveness, it is initially validated using various scheduling problems from the
literature. Then, the model is applied to progressively challenging instances of the shipbuilding
problem presented in this work. Finally, the optimization results are validated and analyzed using
a comprehensive simulation model. Overall, this work contributes to reducing the gap between
academia and industry by providing evidence of the convenience of the application of constrained
programming models combined with simulation models on industrial-size scheduling problems
within reasonable computational time. Moreover, the paper emphasizes originality by addressing
unexplored aspects of shipbuilding scheduling problems and highlights potential future research,
providing a robust foundation for further advancements in the field.
Keywords
Shipbuilding
MILP
CP
Scheduling
Optimization
MILP
CP
Scheduling
Optimization
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CC BY
https://creativecommons.org/licenses/by/4.0/
ISSN
2077-1312