Algorithm Optimization Based on Access Frequency and Task Sequence in the Field of Material Management

Abstract

Conference Title: 2025 17th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

Conference Start Date: 2025 Aug. 22

Conference End Date: 2025 Aug. 23

Conference Location: Hangzhou, China

In the field of material management, in order to improve the operational efficiency of material management, optimizing the storage and picking process has become an important task in the modern supply chain. Previous studies have compared algorithms such as simulated annealing algorithms, genetic algorithms, and particle optimization. However, most of the studies are limited to simulation experiments through software, and have not been verified and explored under the consideration of the frequency and demand of item retrieval. This study aims to explore the improvement of the algorithm by adding the two factors of retrieval frequency and retrieval tasks, and to conduct real-person experimental simulations by building an experimental environment to explore whether the algorithm still has advantages over manual strategies in improving material management efficiency. The results show that the storage strategy optimized by the improved algorithm is significantly lower than the manual strategy in terms of retrieval time. It confirms that the algorithm strategy is a necessary measure in improving material management performance.task may be related to the allocation of attention resources.