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Multi-Period Maximal Covering Location Problem with Capacitated Facilities and Modules for Natural Disaster Relief Services

机译:用于自然救灾服务的电容设施和模块的多周期最大覆盖位置问题

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摘要

The paper aims to study a multi-period maximal covering location problem with the configuration of different types of facilities, as an extension of the classical maximal covering location problem (MCLP). The proposed model can have applications such as locating disaster relief facilities, hospitals, and chain supermarkets. The facilities are supposed to be comprised of various units, called the modules. The modules have different sizes and can transfer between facilities during the planning horizon according to demand variation. Both the facilities and modules are capacitated as a real-life fact. To solve the problem, two upper bounds—(LR1) and (LR2)—and Lagrangian decomposition (LD) are developed. Two lower bounds are computed from feasible solutions obtained from (LR1), (LR2), and (LD) and a novel heuristic algorithm. The results demonstrate that the LD method combined with the lower bound obtained from the developed heuristic method (LD-HLB) shows better performance and is preferred to solve both small- and large-scale problems in terms of bound tightness and efficiency especially for solving large-scale problems. The upper bounds and lower bounds generated by the solution procedures can be used as the profit approximation by the managerial executives in their decision-making process.
机译:本文旨在研究覆盖位置问题与不同类型的设备的结构的多周期最大,如经典的最大覆盖问题(MCLP)的延伸。该模型可以应用,如定位救灾设施,医院和连锁超市。这些设施都应该是由各个单位,称为模块。该模块有不同的尺寸,并根据需求变化的规划周期期间设施之间的可转移。无论是设备和模块获能为现实生活中的事实。为了解决这个问题,两个上部bounds-(LR1)和(LR2) - 和拉格朗日分解(LD)的开发。两个下界从(LR2)从(LR1)获得可行解,和(LD)和一种新颖的启发式算法来计算。该结果表明,该LD方法与下界从发达启发式方法得到(LD-HLB)示出了更好的性能组合,并且优选的是解决这两个小型和大型的问题在结合的紧密度和效率方面尤其解决大进制问题。上界和通过溶液过程中产生下限可被用作通过在他们的决策过程的管理高管利润近似。

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