Optimization analysis of mine car scheduling based on fruit fly optimization algorithm and improved immune particle swarm optimization algorithm

With the rapid development of intelligent technology, the traditional open-pit mining car scheduling system has been unable to meet the needs of efficiency, cost and intelligence. Aiming at the problems of low efficiency and high operating cost of the mine car scheduling system, this paper proposed a mine car scheduling system based on fruit fly optimization algorithm and improved immune particle swarm optimization algorithm. By integrating the concentration regulation mechanism and combining the maximum particle concentration value, the number of sub-populations is adjusted, and the search range of vaccination is adjusted by using the maximum particle concentration value. The results show that the proposed algorithm has better convergence accuracy and global search ability, and can be well applied to the mining car scheduling system, which is of great significance for improving transportation efficiency, ensuring production safety, reducing operating costs, optimizing resource allocation and improving management level.