基于蚁群优化算法的多级应急响应下灾后应急资源空间优化配置  

Post-disaster emergency resource location and allocation based on the ant colony optimal algorithm for multi-level emergency responses

作　　者：文仁强[1] 陈建国[1] 袁宏永[1] 黄全义[1] 

机构地区：[1]清华大学工程物理系,北京100084

出　　处：《清华大学学报（自然科学版）》2012年第11期1591-1596,共6页Journal of Tsinghua University(Science and Technology)

基　　金：国家科技支撑计划项目(2008BAB29B07);国家自然科学基金资助项目(70801039)

摘　　要：灾后多地提出资源需求,在资源有限的情况下为了优先满足重灾区、最大程度覆盖并满足灾区的资源需求,提出了多级应急响应等级,对灾区资源的需求响应进行分级。建立了具有7个优化目标的应急资源空间优化配置数学模型,在模型中考虑了选址点的交通便利度和稳定度,提升了模型的实用性。模型将选址与资源配置进行了统一考虑,并提出了保守型和乐观型资源配置策略,解决了资源充足与受限情况下的优化配置问题。基于Pareto设计的信息素更新规则能够最大程度地减少对多目标优化问题先验知识的依赖,精英档案的引入增强了算法的探索性,加快了全局非劣解搜索速度。算例分析表明,本算法能够很好地处理大型复杂网络。Post-disaster recovery resources are always limited in disaster areas. With limited resources, multi level emergency responses give priority to meeting resource requirements in the hardest hit area in time and to maximizing the resource service coverage in the disaster area. The responses for meeting resource requirements in disaster areas are normally classified. An emergency resource location and allocation optimization model is developed with seven objects. Traffic convenience and stability are taken into account to enhance the applicability of the math model. The location problem and allocation problem are solved as an integrated problem. Then, positive and pessimistic resource allocation strategies are presented to solve the allocation optimization problem for adequate and constrained resources. The pheromone update rules （local and global update rules） are designed to minimize dependence on prior knowledge in multi-objective optimization problems. The elite document and elite strategy are introduced into the algorithm to enhance the search space exploration and accelerate the search speed for the global non-in{erior solution. A practical example is presented to verify the algorithm validity, which shows that the algorithm can handle large complex networks.

关 键 词：资源优化配置 蚁群优化 多级应急响应 应急资源 

分 类 号：X913.1[环境科学与工程—安全科学]