Answering Min-Max Resource-Constrained Shortest Path Queries Over Large Graphs

The constrained shortest path problem is a fundamental and challenging task in applications built on graphs. In this paper, we formalize and study the <inline-formula><tex-math notation="LaTeX">Min</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi>&...

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Veröffentlicht in:IEEE transactions on knowledge and data engineering Jg. 37; H. 1; S. 60 - 74
Hauptverfasser: Qian, Haoran, Zheng, Weiguo, Zhang, Zhijie, Fu, Bo
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.01.2025
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<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> Min</tex-math> <mml:math> <mml:mrow> <mml:mi>M</mml:mi> <mml:mi>i</mml:mi> <mml:mi>n</mml:mi> </mml:mrow> </mml:math> <inline-graphic xlink:href="qian-ieq6-3488095.gif" xlink:type="simple"/> </inline-formula> </named-content>-<inline-formula xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"> <tex-math notation="LaTeX"> Max</tex-math> <mml:math> <mml:mrow> <mml:mi>M</mml:mi> <mml:mi>a</mml:mi> <mml:mi>x</mml:mi> </mml:mrow> </mml:math> <inline-graphic xlink:href="qian-ieq7-3488095.gif" xlink:type="simple"/> </inline-formula> constraint
Accuracy
ancestor checking
Correlation
Costs
Delays
graph algorithms
incremental search
Intellectual property
Search problems
Shortest path problem
shortest path query
Time factors
Valves
Vehicle routing
ISSN:1041-4347, 1558-2191
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Zusammenfassung:The constrained shortest path problem is a fundamental and challenging task in applications built on graphs. In this paper, we formalize and study the <inline-formula><tex-math notation="LaTeX">Min</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="qian-ieq1-3488095.gif"/> </inline-formula>-<inline-formula><tex-math notation="LaTeX">Max</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="qian-ieq2-3488095.gif"/> </inline-formula> resource-constrained shortest path (<inline-formula><tex-math notation="LaTeX">Min</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="qian-ieq3-3488095.gif"/> </inline-formula>-<inline-formula><tex-math notation="LaTeX">Max</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="qian-ieq4-3488095.gif"/> </inline-formula> RCSP) problem, which generalizes the well-studied <inline-formula><tex-math notation="LaTeX">Max</tex-math> <mml:math><mml:mrow><mml:mi>M</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="qian-ieq5-3488095.gif"/> </inline-formula> RCSP problem. The objective is to find a simple path of minimum cost between two query nodes, subject to resource constraints between minimum and maximum limits. This problem has wide applications in fields such as delay networks and transportation. However, we theoretically prove that computing the optimal solution is NP-hard. We propose a two-stage approach that involves resource-based graph reduction followed by cost-guided path generation. To reduce the cost of expensive acyclicity checking, we introduce the technique of ancestor checking based on the shortest path tree. Furthermore, we present an even faster incremental search approach that considers both the path cost and resource constraints while avoiding acyclicity checking. Extensive experiments on twenty real graphs consistently demonstrate the superiority of our proposed methods, achieving up to two orders of magnitude improvement in time efficiency over the baseline algorithms while producing high-quality solutions.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2024.3488095