Title: A multi-objective emergency vehicle scheduling optimisation model

Authors: Jiao Yao; Chuwei Shao; Xiaomei Xia; Pincheng Wang; Yu Wei; Jin Wang

Addresses: Business School, University of Shanghai for Science & Technology, No. 334, Jungong Road, Yangpu District, Shanghai, China ' Business School, University of Shanghai for Science & Technology, No. 334, Jungong Road, Yangpu District, Shanghai, China ' Business School, University of Shanghai for Science & Technology, No. 334, Jungong Road, Yangpu District, Shanghai, China ' Business School, University of Shanghai for Science & Technology, No. 334, Jungong Road, Yangpu District, Shanghai, China ' Business School, University of Shanghai for Science & Technology, No. 334, Jungong Road, Yangpu District, Shanghai, China ' School of Computer and Communication Engineering, Changsha University of Science and Technology, No. 960, South Road Wangjiali, Changsha, 410114, China

Abstract: Various types of emergencies incidents occur frequently, which may cause casualties and huge economic losses. How to optimise the scheduling of emergency rescue vehicles and improve their rescue efficiency is of great significance. Based on the analysis of its influencing factors the emergency vehicle scheduling optimisation model was firstly established, which was oriented to achieve three objects, minimising total travel time, total cost of dispatching travel, and maximising the path reliability. Moreover, the model was solved by Non-dominated Sorting Genetic Algorithm with elite strategy (NSGA-II algorithm). Finally, the local road network in Huangpu District, Shanghai, China was taken as to verify the model in this study. The results show that the optimal solution of the model can achieve the optimal total travel time, and total travel cost and path reliability of the scheduling scheme can also satisfy requirements, which means good validity and practicability.

Keywords: emergency vehicle; scheduling optimisation model; multi-objective planning; NSGA-II algorithm; effectiveness; coefficient; comprehensive evaluation method; influencing factors; travel time; cost of scheduling; path reliability.

DOI: 10.1504/IJSNET.2020.111783

International Journal of Sensor Networks, 2020 Vol.34 No.4, pp.236 - 243

Received: 20 Mar 2020
Accepted: 09 May 2020
Published online: 14 Dec 2020 *

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