摘要
为给决策者在不确定环境下设计具有鲁棒性的应急设施选址布局网络提供决策支持,研究应急设施选址多级覆盖鲁棒优化问题.考虑不确定需求和应急设施多级覆盖响应,建立共享不确定需求和中断情景下服务能力有限的应急设施多级覆盖选址鲁棒优化模型,利用灰狼优化算法(GWO)求解模型,对需求的扰动及应急设施的服务能力进行灵敏度分析.通过随机生成的数值算例验证模型和算法的可行性.结果表明:该模型能有效解决需求不确定和中断风险下选址布局网络的构建问题,且能保证选址决策具有良好的鲁棒性,决策者可基于不同的风险偏好和具体实际在可靠性和系统总成本之间权衡,确定最优的选址分配方案.
In order to provide decision support for decision makers in designing robust emergency facility location network under uncertain environment, a robust hierarchical covering problem for reliability emergency facility location was studied. Based on uncertain demand and hierarchical coverage response, a robust hierarchical covering location model for sharing uncertain demand parameters and limited service capacity was established in presence of probable disruptions. Grey Wolf Optimizer(GWO) was presented to solve the model, the sensitivity analysis of the demand disturbance and the serviceability of the emergency facility were carried out. The feasibility of the model and algorithm was verified by a randomly generated numerical example. The results show that this model can solve the construction problem of location network effectively under uncertain demand and disruption risk, and ensure good robustness of location decision-making. The decision makers can determine the optimal location-allocation scheme based on different risk preferences and actual conditions, which is a trade-off between reliability and total cost.
作者
于冬梅
高雷阜
赵世杰
YU Dongmei;GAO Leifu;ZHAO Shijie(School of Mathematics and System Sciences, Beihang University, Beijing 100191, China;Institute for Optimization and Decision Analytics, Liaoning Technical University, Fuxin, Liaoning 123000, China)
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2019年第4期919-927,共9页
Journal of China University of Mining & Technology
基金
中国博士后基金第65批面上项目(2019M650449)
辽宁省教育厅辽宁省高等学校基本科研项目(LJ2017QL031)
辽宁省博士启动基金项目(20170520075)
2019年度辽宁省自然科学基金指导计划项目
关键词
应急设施选址
不确定需求
多级覆盖
鲁棒优化
灰狼算法(GWO)
emergency facility location
demand uncertainty
hierarchical covering
robust optimization
Grey Wolf Optimizer(GWO)