Optimization of spare parts configuration scheme for ship equipment based on multi-agent simulation

This paper presents a comprehensive exploration of the optimization of spare parts configuration schemes for ship equipment using a multi-agent simulation methodology. The focus lies in leveraging the failure rates of life-limited parts and employing advanced multi-agent modeling technologies to conduct simulated calculations pertaining to a ship's offshore operations. Through these simulations, the paper aims to ascertain the optimal outcomes for the spare parts configuration scheme. The research methodology involves the development and application of a multi-agent simulation method, specifically tailored to address the challenges associated with the mathematical modeling of complex systems. The proposed approach not only enhances the accuracy of spare parts configuration but also contributes to overcoming difficulties in modeling intricate systems. To substantiate the effectiveness of the proposed multi-agent simulation method, the paper includes illustrative examples demonstrating its application in real-world scenarios. The findings of the research highlight the method's efficacy in optimizing spare parts configuration schemes for ship equipment. This paper contributes to the field by presenting a sophisticated and practical approach to address the complexities inherent in mathematical modeling within the context of maritime operations. Based on the multi-agent simulation method, this paper primarily discusses the optimization of spare parts configuration schemes for ship equipment. By means of failure rates of life-limited parts as well as multi-agent modeling technologies, this method can be employed to perform the simulating calculation of a ship's offshore operations, thus determining the optimization outcomes of the spare parts configuration scheme. Research findings demonstrate that the multi-agent simulation method proposed in this paper addresses the difficulties related to the mathematical modeling of complex systems, with an example presented to illustrate the proposed method.