Developing and Planning Department, Yellow River Conservancy Technical Institute, Kaifeng 475004, China.
Comput Intell Neurosci. 2022 Jun 8;2022:7930553. doi: 10.1155/2022/7930553. eCollection 2022.
At present, e-commerce drives the logistics industry to develop greatly, but at the same time, there is a huge demand in this field, such as lower cost and higher efficiency. Facing the needs of logistics management development, it needs the blessing of intelligent technology, which involves countless fields at present. Intelligent logistics management has become a hot spot at present. What needs to be solved in this respect is how to shorten the transportation distance and save costs. To solve this problem, this paper proposes to introduce the shortest path algorithm. This paper compares the Dijkstra algorithm with the A algorithm under the background of logistics management and finds that the latter is more suitable for this field with huge amount of information. In order to improve the performance of the A algorithm, this paper introduces ant colony algorithm, which can better avoid obstacles. Combining these two algorithms, a -ant colony algorithm is obtained. The algorithm absorbs the advantages of the two algorithms, while maintaining high efficiency and good stability. These characteristics are very satisfying in the field of logistics management. Through the performance test and simulation experiment, it is concluded that the algorithm has excellent optimization ability and can reduce the cost for this field.
目前，电子商务推动了物流行业的极大发展，但与此同时，该领域存在着巨大的需求，例如降低成本和提高效率。面对物流管理发展的需求，它需要智能技术的加持，而目前这涉及到无数领域。智能物流管理已成为当前的热点。在这方面需要解决的是如何缩短运输距离和节省成本。为了解决这个问题，本文提出引入最短路径算法。本文在物流管理背景下比较了 Dijkstra 算法和 A算法，发现后者更适合信息量巨大的这个领域。为了提高 A算法的性能，本文引入了蚁群算法，它可以更好地避免障碍。结合这两种算法，得到了 A*-蚁群算法。该算法吸收了两种算法的优点，同时保持了高效率和良好的稳定性。这些特性在物流管理领域非常令人满意。通过性能测试和模拟实验，得出该算法具有出色的优化能力，可以为该领域降低成本。
