A Study on Dynamic Return and Build Strategies for Ambulances Based on an Approximate Hypercube Model

Abstract

With the ageing population and the accelerating pace of urbanization, the demand for emergency medical services is experiencing sustained rapid growth. The traditional resource allocation model of ‘fixed stations plus return to base’ struggles to adapt to the dual time-varying characteristics of both resources and demand, resulting in an increasingly acute imbalance between supply and demand. This paper focuses on the dynamic return-to-base decision-making problem for ambulances that do not return to their original station upon completing a mission, and proposes a dynamic return-to-base strategy based on the Jarvis approximate hypercube model.This study advances ambulance return strategies from ‘static rule optimization to ‘dynamic online decision-making’, achieving an improvement from ‘single-objective’ to ‘multi-objective’ approaches, thereby providing theoretical and methodological support for the dynamic allocation of emergency resources