需求不确定条件下社区应急疏散协作调度优化模型

doi:10.12005/orms.2019.0179

运筹与管理 ›› 2019, Vol. 28 ›› Issue (8): 93-99.DOI: 10.12005/orms.2019.0179

需求不确定条件下社区应急疏散协作调度优化模型

张佰尚^1,2, 付文飙¹, 唐攀², 闪四清³, 尹如法⁴

1.国家市场监督管理总局发展研究中心,北京 100088;
2.暨南大学应急管理研究中心,广东广州 510632;
3.北京航空航天大学经济管理学院,北京 100083;
4.中国建筑科学研究院有限公司建筑机械化研究分院,河北廊坊 065000

收稿日期:2017-10-02 出版日期:2019-08-25
作者简介:张佰尚(1984-),男,河南安阳人,博士,助理研究员,研究方向:决策支持系统;付文飙(1971-),男,吉林长春人,硕士,国家市场监督管理总局发展研究中心主任,研究方向:公共管理;唐攀(1983-),通讯作者,男,湖北武汉人,副教授、博士生导师,研究方向:应急管理;闪四清(1965-),共同通讯作者,男,回族,北京人,教授、博士生导师,研究方向:应急管理信息系统;尹如法(1988-),女,陕西渭南人,工程师,研究方向:科技管理。
基金资助:
国家自然科学基金资助项目(71774068)

Collaborative Scheduling Optimization Model for Community Evacuation under Demand Uncertainty Condition

ZHANG Bai-shang^1,2, FU Wen-biao¹, TANG Pan², SHAN Si-qing³, YIN Ru-fa⁴

1.Development Research Center of State Administration for Market Regulation of the People’s Republic of China, Beijing 100088, China;
2.Emergency Management Research Center, Jinan University, Guangzhou 510632, China;
3.School of Economics and Management, Beihang University,Beijing 100083, China;
4.Institute of Building Mechanization, China Academy of Building Research, Langfang 065000, China

Received:2017-10-02 Online:2019-08-25

摘要/Abstract

摘要： 质量安全、自然灾害、公共卫生等突发事件社区应急疏散中的灾民数量具有不确定性,但目前的研究很少关注多种运输方式协作的应急疏散中灾民数量的不确定性。针对灾民数量的不确定性,以疏散灾民数量最大化,以及疏散成本最小化作为优化目标,,该文构建了多种运输方式协作的社区应急疏散模糊机会约束规划模型。在模型求解时,论文使用自适应遗传算子对多目标遗传算法进行改进,以提高算法优化效率。最后,论文使用算例对提出的模型进行验证,证明了该模型和方法可以有效完成需求不确定条件下的社区应急疏散协作调度优化工作。

关键词: 社区应急疏散, 模糊动态需求, 模糊机会约束规划, 多目标遗传算法

Abstract: For recent years, incidents have hit communities frequently. How to complete the task of resident evacuation is an important problem in public administration. Besides the requirement of varieties of transport tools for collaborative transportation, community evacuation is often characterized by the uncertainty of resident quantity. However, the current studies neither pay much attention to collaboration mode of evacuation with varieties of transportation tools nor consider the uncertainty of resident quantity. Considering the uncertainty caused by resident quantity, this paper constructs fuzzy chance constrained programming model for community evacuation through the coordination of varieties of transportation tools, aiming to accomplish the targets of evacuated victims maximized and evacuation cost minimized. Importantly, this paper designs adaptive genetic operators to improve multi-objective genetic algorithms to enhance the optimization efficiency. Lastly, this paper takes an example to test the proposed model, which proves the proposed model and method have high efficiency in the collaborative scheduling optimization for community evacuation under the condition of uncertainty demand.

Key words: community evacuation, fuzzy dynamic demand, fuzzy chance-constraint programming, multi-objective genetic algorithm

中图分类号:

TP399

张佰尚, 付文飙, 唐攀, 闪四清, 尹如法. 需求不确定条件下社区应急疏散协作调度优化模型[J]. 运筹与管理, 2019, 28(8): 93-99.

ZHANG Bai-shang, FU Wen-biao, TANG Pan, SHAN Si-qing, YIN Ru-fa. Collaborative Scheduling Optimization Model for Community Evacuation under Demand Uncertainty Condition[J]. Operations Research and Management Science, 2019, 28(8): 93-99.

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需求不确定条件下社区应急疏散协作调度优化模型

Collaborative Scheduling Optimization Model for Community Evacuation under Demand Uncertainty Condition

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