A swarm optimization algorithm for practical container loading problem

3D container loading problem (3D-CLP) is a classic NP-hard optimization problem. Although computer scientists and discrete mathematicians have studied this problem for decades, there are still some unsolved puzzles, such as multi-constrained 3D container loading optimization. Moreover, with the rapid development of modern logistics, several new 3D container-loading related problems emerged, such as containers with various sizes, considering different orientations of boxes, and two-step 3D container loading with pallets. From the perspective of practical applications, this paper proposes a new heuristic algorithm for emerged 3D container loading problems. Our proposed algorithm regards the loading arrangement as the position of an individual in the swarm, and by the interactions of the individuals with each other and with loading constraints, most of them will gather to the good ones and finally stop at the best position, which is the loading arrangement of boxes. The proposed algorithm can solve both the 3D container loading problem with pallets or without pallets. Experimental results show significant performance improvements over other state-of-the-art approaches.