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We analyze a distributed approach for automatically reconfiguring distribution systems into an operational radial network after a fault occurs by creating an ordering in which switches automatically close upon detection of a downstream fault. The switches reconnection ordering significantly impacts the expected time to reconnect under normal disruptions and thus affects reliability metrics such as SAIDI and CAIDI, which are the basis for regulator-imposed financial incentives for performance. We model the problem of finding a switch reconnection ordering that minimizes SAIDI and the expected reconnection time as Minimum Reconnection Time (MRT), which we show is a special case of the well-known minimum linear ordering problem from the submodular optimization literature, and in particular the Min Sum Set Cover problem (MSSC). We prove that MRT is also NP-hard. We generalize the kernel-based rounding approaches of Bansal et al. for Min Sum Vertex Cover to give tight approximation guarantees for MSSC on c-uniform hypergraphs for all c. For all instances of MSSC, our methods have a strictly better approximation ratio guarantee than the best possible methods for general MSSC. Finally, we consider optimizing multiple metrics simultaneously using local search methods that also reconfigure the systems base tree to ensure fairness in service disruptions and reconnection times and reduce energy loss. We computationally validate our approach on the NREL SMART-DS Greensboro synthetic urban-suburban network. We evaluate the performance of our reconfiguration methods and show significant reductions compared to single-metric-based optimizations.
In this paper, we consider the Minimum-Load $k$-Clustering/Facility Location (MLkC) problem where we are given a set $P$ of $n$ points in a metric space that we have to cluster and an integer $k$ that denotes the number of clusters. Additionally, we
For each integer $n$ we present an explicit formulation of a compact linear program, with $O(n^3)$ variables and constraints, which determines the satisfiability of any 2SAT formula with $n$ boolean variables by a single linear optimization. This con
Inspired by the decomposition in the hybrid quantum-classical optimization algorithm we introduced in arXiv:1902.04215, we propose here a new (fully classical) approach to solving certain non-convex integer programs using Graver bases. This method is
Analysis of opinion dynamics in social networks plays an important role in todays life. For applications such as predicting users political preference, it is particularly important to be able to analyze the dynamics of competing opinions. While obser
We consider a linear relaxation of a generalized minimum-cost network flow problem with binary input dependencies. In this model the flows through certain arcs are bounded by linear (or more generally, piecewise linear concave) functions of the flows