Multi-strategy hybrid heuristic algorithm for single container weakly heterogeneous loading problem

Three-dimensional single container weakly heterogeneous loading problem is one of the most classical tasks which has various applications in manufacture and logistics industry. Solving this problem could improve transportation efficiency to bring great benefit to shipping customers. During the last two decades, many heuristic, meta-heuristic and hybrid algorithms have been proposed to maximize container volume utilization to reduce the waste of container space significantly. Despite their success in many real-world applications, it is still a challenging task to recommend satisfactory loading levels within a limited time frame when clients approach for options of different combinations of shipping items. In this paper, we propose a novel multistrategy hybrid heuristic algorithm to achieve timely planning for clients in a required short time frame. In specific, a probabilistic model is used to combine the strength of two optimization strategies, i.e. an ant colony method and a constructive greedy method, to speed up the optimization process and ensure better convergence. In addition, a tree pruning strategy is designed to further improve the efficiency of the hybrid heuristic algorithm. Extensive experiments demonstrate the effectiveness of our method in terms of both volume utilization rate and algorithm processing speed compared to state-of-the-art methods. Based on the comparison results by using BR dataset, we achieved averagely 94.31% volume utilization rate and 50.16 seconds processing speed, which is the best performance by considering both algorithm effectiveness and efficiency. Further, our proposed method has been deployed in a real business case to provide plan solutions to individual customer shipping requests and achieved high customer satisfaction rate.