Simultaneous Facility Location and Path Optimization in Static and Dynamic Networks
Simultaneous Facility Location and Path Optimization in Static and Dynamic Networks
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DOI：
10.1109/tcns.2020.2995831
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发表时间：
2020-12
影响因子：
4.2
通讯作者：
Amber Srivastava;S. Salapaka
中科院分区：
文献类型：
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作者：
Amber Srivastava;S. Salapaka
我们提出了一个框架，同时解决静态和动态空间网络中的设施定位和路径优化问题。在静态设置中，目标是确定设施位置和通过设施网络从每个节点到目的地的运输路径，使得商品运输的总成本最小化。这是一个NP难问题。我们提出了一个新的阶段明智的路径，这是在我们的框架中设计的决策变量空间的观点。我们使用最大熵原理来解决由此产生的优化问题。在动态设置中，节点和目的地是动态的。我们设计了一个适当的控制李雅普诺夫函数，以确定时间演变的设施和路径，使运输成本在每个时刻最小化。我们的框架，使量化的设施和运输环节的决策变量方面的属性。因此，可以将应用程序特定的约束纳入各个设施、链路和网络拓扑。我们证明了我们提出的框架的有效性，通过广泛的模拟。
We present a framework for solving simultaneously the problems of facility location and path optimization in static and dynamic spatial networks. In the static setting, the objective is to determine facility locations and transportation paths from each node to the destination via the network of facilities such that the total cost of commodity transportation is minimized. This is an NP-hard problem. We propose a novel stage-wise viewpoint of the paths which is instrumental in designing the decision variable space in our framework. We use the maximum entropy principle to solve the resulting optimization problem. In the dynamic setting, nodes and destinations are dynamic. We design an appropriate control Lyapunov function to determine the time evolution of facilities and paths such that the transportation cost at each time instant is minimized. Our framework enables quantifying attributes of the facilities and transportation links in terms of the decision variables. Consequently, it becomes possible to incorporate application specific constraints on individual facilities, links, and network topology. We demonstrate the efficacy of our proposed framework through extensive simulations.