Operations Research and Management Science ›› 2019, Vol. 28 ›› Issue (1): 71-78.DOI: 10.12005/orms.2019.0009

• Theory Analysis and Methodology Study • Previous Articles     Next Articles

A Decision Model of Reserve Coverage Selection for Multi-level Service Facilities Based on Improved NSGA-II Algorithm

SONG Yan, TENG Chen-mei, JIANG Jin-gui   

  1. School of Economics and Management, Harbin Engineering University, Harbin 150001, China
  • Received:2016-11-23 Online:2019-01-25

基于改进NSGA-II算法的多级服务设施备用覆盖选址决策模型

宋艳, 滕辰妹, 姜金贵   

  1. 哈尔滨工程大学 经济管理学院,黑龙江 哈尔滨 150001
  • 作者简介:宋艳(1974-),女,吉林榆树人,教授,博士,研究方向:管理信息系统、危机与灾害管理、城镇化等;滕辰妹(1991-),女,山东日照人,博士研究生,研究方向:选址决策与布局优化;姜金贵(1980-),男,黑龙江哈尔滨人,副教授,博士,研究方向:危机响应与管理信息系统。
  • 基金资助:
    黑龙江省软科学项目(GC16D104);哈尔滨工程大学校基金项目(HEUCFW170903)

Abstract: In order to deal with the problem of differentiated demand of disaster service in the process of cross-regional emergencies, a multi-level reserve coverage decision model of emergency reserve facilities is established, that is, a demand point is provided by different emergency facilities. In the process of modeling, the situation of the service provided by other facilities is considered in the busy state of the facility, which makes the model more practical. For the first time, the NSGA-II algorithm is improved by designing the segmented chromosome coding method to improve the operation efficiency to solve the multi-target location decision problem. The Pareto solution distribution obtained under the improved method is compared with the simulation results under the NSGA-II algorithm, and the spatial distribution scheme is obtained according to the deployment strategy of the facility. It proves the feasibility of the model and the effectiveness of the improved NSGA-II algorithm in solving the multi-objective location decision-making problem. The model can provide a valid basis for the decision-makers to a certain extent.

Key words: differentiated demand, multi-level backup coverage model, chromosome coding, improved NSGA-II algorithm

摘要: 为了应对跨区域突发事件过程中受灾点服务差异化需求的问题,建立了应急储备设施点的多级备用覆盖选址决策模型,即一个需求点由多个应急设施提供不同质量水平的服务,并考虑设施繁忙状态下由其他设施点提供服务的状况,使模型更加符合实际应用。首次通过设计分段的染色体编码方式改进NSGA-II算法提升运算效率以更好地解决多目标选址决策问题,将改进方法下得到的Pareto解分布与NSGA-II算法下的仿真结果进行对比分析,结合设施点的部署策略得到不同的空间布局方案。证明了模型的可行性及改进NSGA-II算法在解决设施点多目标选址决策问题时的有效性。

关键词: 差异化需求, 多级备用覆盖模型, 染色体编码, 改进NSGA-II算法

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