Multi-Supply Points Combination Sequence Optimization and Discrete Multi-Strategy Sparrow Algorithm in Emergency Logistics

Following major disasters, the urgent demand for supplies often overwhelms the capacity of single reserve points, necessitating the simultaneous coordination of resources from multiple reserve points. While prior studies have focused on evaluating and selecting individual points, the complex dynamics of coordinating multiple reserve points for joint supply remain underexplored.This paper develops a model for optimizing emergency logistics capabilities by determining the most effective sequence of supply point combinations. This study's innovation lies in addressing the dynamic cost variations of the same supply points under different combinations. Factors such as transportation distance, connection costs, and the shifting relative locations with other supply points contribute to diverse outcomes. Additionally, transfer and connection costs among supply points are incorporated to reflect realistic logistical challenges.Another contribution is the Discrete Multi-Strategy Sparrow Algorithm (DMSSA), an enhanced version of the sparrow search algorithm, developed to solve the constructed model and ascertain the optimal supply point combination sequence. Through discretization and feasibility improvements, DMSSA addresses key limitations of the original algorithm, including inadequate global search ability and susceptibility to local optima. By integrating four mutation strategies, experimental results demonstrate that DMSSA significantly improves sophistication and optimization capabilities, consistently outperforming five widely used intelligent algorithms.