Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (13): 153-159.DOI: 10.3778/j.issn.1002-8331.1702-0215

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Ambulance emergency rescue routing planning for improved ant colony algorithm

KONG Lin1, ZHANG Guofu1,2, SU Zhaopin1,2, JIANG Jianguo1,2   

  1. 1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China
    2.Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of Education, Hefei 230009, China
  • Online:2018-07-01 Published:2018-07-17


孔  林1,张国富1,2,苏兆品1,2,蒋建国1,2   

  1. 1.合肥工业大学 计算机与信息学院,合肥 230009
    2.安全关键工业测控技术教育部工程研究中心,合肥 230009

Abstract: The parallel scheduling of ambulance and the problem of mass casualty rescue have been the priority problem in the field of emergency rescue. This paper firstly cites a model of ambulance concurrent allocation and scheduling optimization for a number of wounded patients with different degree of injury, according to the severity of the injury will be the classification of all the injured, on the basis of this different priorities for ambulance scheduling and rescue. In the heuristic algorithm, Ant Colony Optimization(ACO) pheromone global update strategy is improved to achieve the simultaneous optimization of multiple scheduling routes. Comparative experiments show that the proposed model and intelligent algorithm has better performance in the case of ambulance resources inadequately, the algorithm can generate a set of effective and feasible solutions and gives the wounded rescue routes and response time to each ambulance.

Key words: ambulance emergency allocation, scheduling routes, Ant Colony Optimization(ACO)

摘要: 救护车并行调度与大规模伤员救援一直是应急救援过程中需要优先解决的问题。引用一种面向多位受伤程度不同的伤员的救护车并发调度与分配优化模型,依据伤情轻重将所有伤者进行分类,按不同优先级进行救护车的调度与救援;采用蚁群优化智能算法求解这个复杂的优化问题。在启发式算法中,改进蚁群优化中的信息素更新策略以实现多个调度路径的同时优化。对比实验表明,所提模型与智能算法在救护车资源不是很充足的情况下具有更好的性能,能够产生一组有效可行的解,并可以同时给出各个救护车响应各伤员的救援路径和响应时间。

关键词: 救护车应急分配, 路径调度, 蚁群优化