应急联动区域下选址分配协同优化模型研究
|
摘要
针对我国现有应急储备库按照属地管理布局的不足,例如当受灾点发生重大灾害时,各应急储备库实行均匀配置,导致应急系统救援效率低以及资源的浪费,文章引入集合覆盖选址模型和"覆盖满意度"思想,将应急联动区域内的服务需求分为第一时间救援服务需求和后续救援服务需求,以应急服务成本最小和覆盖满意度最大为目标,建立应急联动下区域储备库选址分配协同优化模型.对四川省地震灾害下的应急储备库选址分配问题进行案例分析,考虑到各区县抗灾能力的不同,采用TOPSIS方法对模型中受灾点的脆弱性进行评价,并利用NSGA-Ⅱ算法对模型求解.研究表明,模型能降低应急联动区域内的应急服务成本,提升应急服务水平,同时模型可以为决策者提供多种优化方案.
Focus in put on the shortage of the existing emergency reserve under the administrative division structure, Taking the emergency response satisfaction and economy into account, a location and allocation model for regional emergency response is formulated. The objective of this model is to maximize the emergency response satisfaction value as much as possible, addressing the Low efficiency of resource utilization at the same time. By historical earthquake disaster of Sichuan Province, using TOPSIS analysis method to evaluate earthquake disaster vulnerability of the selected area. The improved NSGA-Ⅱ algorithm is used to solve the model. The results of a numerical example prove that the model is feasible and the algorithm is efficient for solving above collaborative location and allocation problem of sectional reserves, which can also offer a variety of decision making options.
Focus in put on the shortage of the existing emergency reserve under the administrative division structure, Taking the emergency response satisfaction and economy into account, a location and allocation model for regional emergency response is formulated. The objective of this model is to maximize the emergency response satisfaction value as much as possible, addressing the Low efficiency of resource utilization at the same time. By historical earthquake disaster of Sichuan Province, using TOPSIS analysis method to evaluate earthquake disaster vulnerability of the selected area. The improved NSGA-Ⅱ algorithm is used to solve the model. The results of a numerical example prove that the model is feasible and the algorithm is efficient for solving above collaborative location and allocation problem of sectional reserves, which can also offer a variety of decision making options.
引文
[1] Calixto E,Larouvere E L. The regional emergency plan requirement:application of the best practices to the brazilian case[J]. Safety Science, 2010(8):991-999.
[2] Balcik B,Beamon B M, Krejci C C,et al. Coordination in humanitarian relief chains:practices,challenges and opportunities[J]. International Journal of Production Economics, 2010(1):22-34.
[3]王薇.跨域突发事件府际合作应急联动机制研究[J].中国行政管理,2016(12):113-117.
[4]王旭,黄炎炎.基于OODA环的城市内涝灾害应急联动体系建模[J].南京理工大学学报,2018(2):234-242.
[5]李伟权,聂喻薇.叠加型风险下整合型应急预警联动机制缺失问题研究——12·20深圳特别重大滑坡事故的教训[J].中国行政管理,2016(9):128-134.
[6]樊博,杨文婷,尹鹏程.应急资源协同对联动信息系统构建的影响机理——基于IS成功模型的分析[J].系统管理学报,2017(5):801-808.
[7]李周清,马祖军.区域性应急物资储备级库间的协同选址模型研究[J].自然灾害学报,2012(2):57-62.
[8]刘诚,陈则辉,龚玉燕.基于时间满意度的应急物资储备库选址问题[J].数学的实践与认识,2014(17):8-14.
[9]王亮,邱玉琢.两级应急物资储备协同预先配置优化决策研究[J].软科学,2015(12):117-120.
[10]李超萍.应急物资储备中片区储备库协同选址研究[J].西华大学学报:自然科学版,2013(4):83-88.
[11]蔡冬雪,朱建明,王国庆.基于情景分析的应急装备多层级协同布局问题研究[J].中国管理科学,2017(10):72-79.
[12] Arora H, Raghu T S, Vinze A. Resource allocation for demand surge mitigation during disaster response[J]. Decision Support Systems, 2010(1):304-315.
[13]孙洋,卢毅,熊先明等.四川省21市州城市自然灾害脆弱性评估研究[J].自然灾害学报,2017(4):116-124.
[14] Deb K. A fast elitist multi-objective genetic algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2000(2):182-197.
[15]冯领香,冯振环.京津冀都市圈地震灾害脆弱性评价及城际差异分析[J].自然灾害学报,2013(3):160-167.
[16]马亚杰,李永义,韩秀丽.基于人工神经网络的地震经济损失评估[J].世界地震工程,2007(1):146-150.
[2] Balcik B,Beamon B M, Krejci C C,et al. Coordination in humanitarian relief chains:practices,challenges and opportunities[J]. International Journal of Production Economics, 2010(1):22-34.
[3]王薇.跨域突发事件府际合作应急联动机制研究[J].中国行政管理,2016(12):113-117.
[4]王旭,黄炎炎.基于OODA环的城市内涝灾害应急联动体系建模[J].南京理工大学学报,2018(2):234-242.
[5]李伟权,聂喻薇.叠加型风险下整合型应急预警联动机制缺失问题研究——12·20深圳特别重大滑坡事故的教训[J].中国行政管理,2016(9):128-134.
[6]樊博,杨文婷,尹鹏程.应急资源协同对联动信息系统构建的影响机理——基于IS成功模型的分析[J].系统管理学报,2017(5):801-808.
[7]李周清,马祖军.区域性应急物资储备级库间的协同选址模型研究[J].自然灾害学报,2012(2):57-62.
[8]刘诚,陈则辉,龚玉燕.基于时间满意度的应急物资储备库选址问题[J].数学的实践与认识,2014(17):8-14.
[9]王亮,邱玉琢.两级应急物资储备协同预先配置优化决策研究[J].软科学,2015(12):117-120.
[10]李超萍.应急物资储备中片区储备库协同选址研究[J].西华大学学报:自然科学版,2013(4):83-88.
[11]蔡冬雪,朱建明,王国庆.基于情景分析的应急装备多层级协同布局问题研究[J].中国管理科学,2017(10):72-79.
[12] Arora H, Raghu T S, Vinze A. Resource allocation for demand surge mitigation during disaster response[J]. Decision Support Systems, 2010(1):304-315.
[13]孙洋,卢毅,熊先明等.四川省21市州城市自然灾害脆弱性评估研究[J].自然灾害学报,2017(4):116-124.
[14] Deb K. A fast elitist multi-objective genetic algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2000(2):182-197.
[15]冯领香,冯振环.京津冀都市圈地震灾害脆弱性评价及城际差异分析[J].自然灾害学报,2013(3):160-167.
[16]马亚杰,李永义,韩秀丽.基于人工神经网络的地震经济损失评估[J].世界地震工程,2007(1):146-150.