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Journal of System Simulation

Abstract

Abstract: To address the issues of low supply chain collaboration efficiency and inadequate dynamic scheduling capability caused by the disconnection between design and procurement in digital shipbuilding, a method integrating multi-agent simulation with the Q-learning reinforcement learning algorithm is proposed, and a four-tier dynamic supply chain model coupling design and procurement is developed, covering mines, steel mills, shipyards, and shipowners. Based on the depth of collaboration, steel mills are classified into three levels, including full collaboration, partial collaboration, and noncollaboration, with differentiated state spaces and reward functions designed to simulate intelligent pricing and game behaviors under information asymmetry. Simulation results show that shipyards need to intelligently adjust collaborative procurement strategies based on the dynamic trade-off between construction cycle and cost. This provides a quantifiable intelligent simulation method and decision-making basis for achieving precise collaboration, dynamic scheduling, and optimized decision-making throughout the entire process from design to procurement execution.

First Page

2857

Last Page

2871

CLC

TH186; TP391

Recommended Citation

Peng Kaitai, Feng Dingyi, Zhao Wenbo, et al. Research on Digital Shipyard Design-procurement Coupling Based on Multi-agent Systems[J]. Journal of System Simulation, 2026, 38(10): 2857-2871.

Corresponding Author

Chen Feier

DOI

10.16182/j.issn1004731x.joss.26-0021

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