Work

Intelligent Emergency Logistics Route Model Based on Cellular Space AGNES Clustering and Symmetrical Fruit Fly Optimization Algorithm

Year: 2025

Type: article

Abstract: In response to the current research status and existing problems of material distribution during major emergency events, we construct an intelligent emergency logistics route model based on cellular space AGNES clustering (AGglomerative NESting clustering) and a symmetrical fruit fly optimization algorithm. We establish the cellular algorithm based on urban road nodes and node local spaces, and construct the topology algorithm to implement the cellular space in a way that includes distribution centers and delivery points. In the cellular space, we develop an improved AGNES clustering algorithm based on the cellular space model in accordance with the neighboring relationship between distribution centers and delivery points, which quantifies the spatial clustering relationship between the distribution centers and the delivery points. Based on the clustering model, we construct an emergency logistics route model by using a symmetrical fruit fly optimization algorithm. In line with the symmetrical feature of a logistics route from one destination to another, the traveling distances within one route section are the same in both directions. Thus, we construct the logistics sub-intervals and logistics intervals by using distribution centers and delivery points, and the optimal fruit fly individuals and corresponding fitness functions are searched within the two-level intervals to obtain the emergency logistics routes with the lowest costs. Experimental results show that the proposed algorithm can output the optimal logistics routes for each logistics sub-interval and the entire logistics interval. Compared with the traditional route planning methods Dijkstra’s algorithm and the A* algorithm, it can reduce the cost of route planning and achieve optimization rates of 9.89% and 13.12%, respectively. The t-test proves that the constructed algorithm is superior to the traditional route planning algorithms in saving route costs.

Source: Symmetry

DOI: 10.3390/sym17050649

Authors: Xiao Zhou, Jun Wang, Wenbing Liu, Fan Jiang, Rui Li

Institutions: Xihua University, Leshan Vocational and Technical College, PLA Army Service Academy

Language: English

Topic: Facility Location and Emergency Management

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896