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Bibliographic Details
Main Authors: Dong, Anqi, Taghvaei, Amirhossein, Georgiou, Tryphon T.
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.22745
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author Dong, Anqi
Taghvaei, Amirhossein
Georgiou, Tryphon T.
author_facet Dong, Anqi
Taghvaei, Amirhossein
Georgiou, Tryphon T.
contents We revisit the problem of finding the shortest path between two selected vertices of a graph and formulate this as an $\ell_1$-regularized regression -- Least Absolute Shrinkage and Selection Operator (lasso). We draw connections between a numerical implementation of this lasso-formulation, using the so-called LARS algorithm, and a more established algorithm known as the bi-directional Dijkstra. Appealing features of our formulation include the applicability of the Alternating Direction of Multiplier Method (ADMM) to the problem to identify short paths, and a relatively efficient update to topological changes.
format Preprint
id arxiv_https___arxiv_org_abs_2511_22745
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A lasso-alternative to Dijkstra's algorithm for identifying short paths in networks
Dong, Anqi
Taghvaei, Amirhossein
Georgiou, Tryphon T.
Optimization and Control
Distributed, Parallel, and Cluster Computing
Social and Information Networks
Image and Video Processing
05C38, 05C50, 05C85, 62J07, 90C25
We revisit the problem of finding the shortest path between two selected vertices of a graph and formulate this as an $\ell_1$-regularized regression -- Least Absolute Shrinkage and Selection Operator (lasso). We draw connections between a numerical implementation of this lasso-formulation, using the so-called LARS algorithm, and a more established algorithm known as the bi-directional Dijkstra. Appealing features of our formulation include the applicability of the Alternating Direction of Multiplier Method (ADMM) to the problem to identify short paths, and a relatively efficient update to topological changes.
title A lasso-alternative to Dijkstra's algorithm for identifying short paths in networks
topic Optimization and Control
Distributed, Parallel, and Cluster Computing
Social and Information Networks
Image and Video Processing
05C38, 05C50, 05C85, 62J07, 90C25
url https://arxiv.org/abs/2511.22745