We consider the problem to transport resources/mass while abiding by constraints on the flow through constrictions along their path between specified terminal distributions. Constrictions, conceptualized as toll stations at specified points, limit the flow rate across. We quantify flow-rate constraints via a bound on a sought probability density of the times that mass-elements cross toll stations and cast the transportation scheduling in a Kantorovich-type of formalism. Recent work by our team focused on the existence of Monge maps for similarly constrained transport minimizing average kinetic energy. The present formulation in this paper, besides being substantially more general, is cast as a (generalized) multi-marginal transport problem - a problem of considerable interest in modern-day machine learning literature and motivated extensive computational analyses. An enabling feature of our formalism is the representation of an average quadratic cost on the speed of transport as a convex constraint that involves crossing times.
翻译:我们考虑的是资源/质量的运输问题,同时要遵守在特定终点分配之间通过限制而限制流动的问题; 限制(概念化为特定点的收费站)限制流动率; 限制(概念化为特定点的收费站)限制流动率; 限制(概念化为在特定点的收费站)限制流动率; 限制(我们根据大规模人口交叉收费站所寻求的概率密度来量化流动率限制; 将运输日程安排定在Kantorovich式的形式主义中; 我们的团队最近的工作重点是为同样受限制的交通绘制蒙盖地图,最大限度地减少平均动能; 本文目前的措辞除了非常笼统外,还被描绘成一个(一般化的)多边运输问题——一个对现代机器学习文献相当感兴趣的问题,并激发广泛的计算分析; 我们形式主义的一个有利特征是,对运输速度的平均四边价代表了涉及穿越时间的锥体限制。