Research and optimization of container explosives packing problem based on hybrid heuristic algorithm

In the container transportation of dangerous goods by sea, a scientific and reasonable loading scheme is crucial to enhance transportation safety. A hybrid particle swarm genetic algorithm based on anthropomorphic loading strategy is proposed for the special fitting and segregation requirements of explosives in dangerous goods, with the goal of minimizing the number of containers required. The hybrid heuristic algorithm combines the global search capability of genetic algorithm and the local optimization capability of particle swarm algorithm and further improves the algorithm performance by introducing population diversity to monitor the search efficiency and convergence of the algorithm. By simulating the packing scenarios of 5 groups of 10 types of explosives cargoes, the algorithm provides a better-quality packing scheme, and less time consumption compared to the genetic algorithm.