救護車動態佈署之隨機最佳化模式

A Stochastic Programming Approach for Ambulance Dynamic Relocation

陳育詩(Yu-Shih Chen)

指導教授 ： 陳柏華

國立臺灣大學/工學院/土木工程學研究所/碩士(2016年)

https://doi.org/10.6342/NTU201602115

摘要

到院前緊急救護服務（EMS）提供患者現場醫療、穩定病況及運送的重要功能，其服務品質可以患者抵達醫院的時間（TAH）作為衡量標準，以短時階需求預測為依據調度救護車可達到降低TAH之目的。因此，本研究旨在整合EMS需求預測方法和救護車調度最佳化模式，建構一個完整動態救護車調度系統，以提升EMS的服務績效。本研究提出救護車動態調度機制、隨機時空路網最佳化模式及拉氏對偶分解之分支界定演算法，透過同時考量未來需求及救護車當下之佈署計畫，提供下一時段更合理之佈署方案，從而輔助救護車重新佈署的即時決策。從研究結果顯示，我們提出的系統及方法具有提升到院前緊急救護服務績效的可能性及實際運用之可行性。

關鍵字

緊急救護服務 ； 救護車動態調度系統 ； 需求預測方法 ； 隨機時空路網最佳化模式 ； 拉氏釋限 ； 對偶分解 ； 分支界定

並列摘要

Pre-hospital Emergency Medical Service (EMS) provides the critical function of on-site medical treatment, stabilization of patients and transportation. In general, the performance of EMS can be measured by the Time of Arrival at Hospital (TAH), defined as the time interval from the dispatch of an ambulance until the arrival of the patient at a hospital. A better management of ambulances can reduce the TAH by taking into consideration of short-term demand forecast. This study aims to propose a dynamic relocation system to integrate EMS demand forecasting and with an ambulance deployment model to decrease the TAH. In our work, we develop a dynamic system, a stochastic spatial temporal network allocation model, and a Lagrangian dual decomposition with branch and bound algorithm to optimize the ambulance operations. By simultaneously considering the forecasting demands and ambulance immediate deployment, we can obtain a more optimized deployment plan for the next time interval. The purpose of the model is to assist close-to-real-time ambulance relocation decisions. The results show that the system and approaches we propose have the potential to enhance the performance of pre-hospital EMS and could be implemented in the real world.

並列關鍵字

Emergency Medical Service ； Ambulance Dynamic Relocation System ； Demand Forecast Method ； Stochastic Spatial Temporal Network Allocation Model ； Lagrangian Relaxation ； Dual Decomposition ； Branch and Bound

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