Research on Container Loading Problem Based on Enhanced Lion Swarm Algorithm

This paper proposes an enhanced lion swarm metaheuristic algorithm with cargo block preprocessing for container loading problems under complex constraints. Considering cargo and spatial characteristics, a data preprocessing algorithm integrating simple and complex blocks is designed to narrow the solution space in advance. A novel state value query method is developed with time complexity controlled at $O(l o g n)$. A residual space merging strategy is introduced to improve container fill rates. Normal distribution adjustment factors and Gaussian perturbation mechanisms are incorporated to enhance algorithmic stochasticity. Lion swarm pairing and mutation optimization rules are specifically tailored for bin-packing scenarios. Experimental simulations on public datasets validate the algorithm’s effectiveness.