设施选址问题
计算机科学
水准点(测量)
启发式
集合(抽象数据类型)
算法
容错
比例(比率)
分布式计算
数学优化
人工智能
数学
物理
地理
程序设计语言
量子力学
大地测量学
标识
DOI:10.1109/ieem55944.2022.9989850
摘要
The design of supply networks that are resilient to disruptions has recently attracted considerable attention. We consider supply networks where a set of clients are served from a set of facilities. The cost of serving a client from a facility is proportional to the distance between the client and the facility. When a facility becomes unavailable due to a disruption, its clients are reassigned to the closest facility that is still operating. The network is resilient when disruptions cause only moderate reassignment costs. One way to design a resilient network is to solve the fault-tolerant k-median problem. Under this problem, a set of k facilities (medians) must be located such that the sum of distances from clients to their r nearest facilities is minimized. This paper introduces a new algorithm for large-scale instances of this problem. Using a benchmark instance with close to 10,000 clients, we demonstrate that our heuristic consistently devises better solutions than the state-of-the-art approach in much shorter running times.
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