Resumen
The issue of unloading efficiency for containers is the operational bottleneck for most traditional container terminals. In addressing the intricate challenges of space allocation in container yards during ship unloading, this study focuses on the real-time, dynamic decision-making needs that are currently unmet by existing planning methods. To tackle this, the article introduces a novel model for container space allocation that aims to maximize the ?attractiveness? of yard spaces. This model factors in key considerations like the allocation of container handling equipment resources, the rate of container handling equipment traversing the yard, and container handling equipment operations across containers. A unique Monte Carlo tree search (MCTS)-based algorithm is developed to solve this multi-objective problem. The algorithm?s efficacy is rigorously tested via numerical experiments, where it outperforms existing approaches like UCT-MCTS, AMAF-MCTS, and manual scheduling plans using practical engineering examples. This research not only provides a more dynamic and efficient method for yard space allocation but also offers empirical evidence to support its practicality and effectiveness.