设施拥堵状态下的层次性备用覆盖网络模型与改进遗传算法

经典的分层覆盖位置问题(HCLP)是在有限预算内找到设施位置以提供分层服务的问题.这个过程中,需求点的差异化服务需求可以来自层次型网络中不同服务可用性的设施.我们设计了混合服务可用性的层次型网络,通过讨论层次型设施数量为定量和变量的情况构建混合层次网络备用覆盖问题的整数规划模型,并设计、改进元启发式算法来求解问题.结果表明考虑变量的混合服务可用性的优化模型在一次覆盖中能更好的满足客户的需求,而其备用覆盖能力和系统造价并非始终优于单类型层次网络;建议的启发式算法在合理的计算时间内产生高质量的解.

Optimal decision model and improved genetic algorithm for disposition of hierarchical facilities under facility congestion

The classical hierarchical covering location problem (HCLP) is the problem to find locations within a limited budget to provide hierarchical services. In general, the ability of a hierarchical facility to export services to an affected area depends on its range of service radii and is not affected by service availability. Instead, this requirement can come from different facilities with different service availability in the hierarchical network. We designed a hierarchical network of hybrid service availability and constructed an integer-programming model for the hybrid hierarchical backup coverage location problem by discussing the number of hierarchical facilities as quantitative and variable, and developed the meta-heuristic algorithm. It is shown that the optimization model meets the needs better in coverage capability, while the backup coverage capability and system cost are not always better than the single-type hierarchical network; and the suggested heuristic yields high quality solution in a reasonable computation time.