Multi-resource Scheduling Problem for Emergency Supplies Based on Improved Sparrow Search Algorithm

Abstract

In order to address the issue of the dispatch of supplies following a major public health event, this paper considers the use of multiple means of transport for the joint movement of materials, a three-tier dispatch network with multiple supply points, multiple distribution centres and multiple demand points is used to achieve multi-cycle, multi-modal and multi-resource dispatch of emergency supplies, with timeliness, dual fairness and comprehensive costs as the objectives. This paper takes the disaster relief demand after a major public health event as the research object, and establishes a multi-objective optimal scheduling model for emergency materials around the problem of emergency relief materials scheduling in disaster areas, good point sets, dynamic inertia weights, polynomial variants and greedy selection strategies are introduced to improve the sparrow algorithm and solve the model. The results show that the improved sparrow algorithm can consistently find the optimal value of the function in a wide range of test functions. Compared with the original algorithm and the grey wolf algorithm, the convergence accuracy is higher, the solution performance is superior, and a more efficient and fair scheduling scheme can be obtained to solve the multimodal and multi-cycle emergency material scheduling problem. As a result, the improved sparrow search algorithm performs well in dealing with more complex emergency material scheduling and demonstrates its significant value and effectiveness in practical applications.