Characterizing Flow Complexity in Transportation Networks Using Graph Homology
Series-parallel networks generally exhibit simplified dynamics, and lend themselves to computationally tractable optimization problems. We are interested in a systematic analysis of the flow complexity that emerges as a network deviates from a series-parallel topology. This letter introduces the not...
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Published in | IEEE control systems letters Vol. 8; pp. 1625 - 1630 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
IEEE
2024
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Subjects | |
Online Access | Get full text |
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Summary: | Series-parallel networks generally exhibit simplified dynamics, and lend themselves to computationally tractable optimization problems. We are interested in a systematic analysis of the flow complexity that emerges as a network deviates from a series-parallel topology. This letter introduces the notion of a robust p-path on a directed acyclic graph to localize and quantify this complexity. We develop a graph homology with robust p-paths as the bases of its p-chain spaces. We expect that this association between the collection of robust p-paths within a graph and an algebraic structure will provide a framework for the analysis of flow networks. To this end, we show that the simplicity of the series-parallel class corresponds to triviality of high-order chain spaces <inline-formula> <tex-math notation="LaTeX">(p\gt 2) </tex-math></inline-formula>. Consequently, the susceptibility of a flow network to the Braess Paradox is associated with the space of 3-chains. Moreover, the computational complexity of decision problems on a network can be related to the order of chains within the proposed homology. |
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ISSN: | 2475-1456 2475-1456 |
DOI: | 10.1109/LCSYS.2024.3413597 |