Research on Optimization Method of Ship Spare Parts Allocation Based on Improved Discrete Crow Search Algorithm

As the main component of maintenance support resources, how to allocate ship spare parts efficiently and reasonably has always been a key research topic. Aiming at the problem that the allocation of ship spare parts is unreasonable and the demand for some spare parts can not be guaranteed in time, the focus of this paper is the optimization of ship spare parts allocation during the execution of tasks. To achieve this goal, we propose a novel optimization approach for spare parts allocation, drawing inspiration from the improved crow search algorithm. Firstly, Monte Carlo simulation is used to determine the initial scheme of spare parts allocation. Then, the limitation of spare parts allocation and the requirement of ship support department are considered comprehensively. Moreover, an optimization model of inventory allocation under multi-constraints is established. The improved discrete crow search algorithm integrating multiple strategies is used to solve the model to determine the optimal optimization scheme for spare parts. Finally, the accuracy and feasibility of the established model are verified by the actual data of ship spare parts, which can provide decision support for making reasonable allocation schemes for ship spare parts.