An efficient all-pairs approach for multi-objective dynamic shortest path problems

The Shortest Path problem is fundamental for determining optimal routes in various applications. The Dynamic Shortest Path problem extends this concept to evolving graph structures. However, existing algorithms often fail to address decision-making complexities involving multiple objectives. In our...

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Vydané v:Neural computing & applications Ročník 37; číslo 30; s. 24823 - 24851
Hlavní autori: da Silva, Juarez Machado, Ramos, Gabriel de Oliveira, Barbosa, Jorge Luis Victória
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Springer London 01.10.2025
Springer Nature B.V
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Abstract The Shortest Path problem is fundamental for determining optimal routes in various applications. The Dynamic Shortest Path problem extends this concept to evolving graph structures. However, existing algorithms often fail to address decision-making complexities involving multiple objectives. In our previous work, we introduced the Multi-Objective Dynamic Shortest Path problem to address this gap. This paper presents the All-pairs Multi-objective Dynamic Shortest Path algorithm, offering a novel approach that combines a labeling-correcting method with the Optimistic Linear Support algorithm. This hybrid methodology enhances efficiency by minimizing redundant calculations during graph updates. Extensive testing demonstrates that our algorithm is over 3.22 times faster than baseline algorithms in producing Pareto solutions. This work advances techniques for multi-objective dynamic shortest paths and tackles challenges in evolving graph structures, paving the way for future research in this dynamic field.
AbstractList The Shortest Path problem is fundamental for determining optimal routes in various applications. The Dynamic Shortest Path problem extends this concept to evolving graph structures. However, existing algorithms often fail to address decision-making complexities involving multiple objectives. In our previous work, we introduced the Multi-Objective Dynamic Shortest Path problem to address this gap. This paper presents the All-pairs Multi-objective Dynamic Shortest Path algorithm, offering a novel approach that combines a labeling-correcting method with the Optimistic Linear Support algorithm. This hybrid methodology enhances efficiency by minimizing redundant calculations during graph updates. Extensive testing demonstrates that our algorithm is over 3.22 times faster than baseline algorithms in producing Pareto solutions. This work advances techniques for multi-objective dynamic shortest paths and tackles challenges in evolving graph structures, paving the way for future research in this dynamic field.
Author da Silva, Juarez Machado
Ramos, Gabriel de Oliveira
Barbosa, Jorge Luis Victória
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Shortest path
Dynamic shortest paths
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Snippet The Shortest Path problem is fundamental for determining optimal routes in various applications. The Dynamic Shortest Path problem extends this concept to...
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SubjectTerms Algorithms
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Decision making
Energy consumption
Image Processing and Computer Vision
Labeling
Multiple objective analysis
Objectives
Probability and Statistics in Computer Science
S.I.: Multi-Objective Decision Making 2023
Shortest-path problems
Special Issue on Multi-Objective Decision Making 2023
Title An efficient all-pairs approach for multi-objective dynamic shortest path problems
URI https://link.springer.com/article/10.1007/s00521-025-11437-6
https://www.proquest.com/docview/3259432172
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