Transportation scheduling algorithm for underground mines based on sparrow search algorithm optimized genetic algorithm

This paper addresses the problem of transporting people and goods in underground mining areas by establishing a mathematical model and proposing a coding and iterative process based on the Sparrow Search Algorithm optimized genetic algorithm. Test cases more aligned with the model were constructed using the CordeauMDVRP benchmark examples. Iterative comparisons were conducted between the basic genetic algorithm and the Sparrow Search Algorithm optimized genetic algorithm, revealing that the Sparrow Search Algorithm optimized genetic algorithm (GSSA) converges faster and avoids falling into local optima, especially with a larger number of nodes.