Efficient Parallel Algorithm for Minimum Cost Submodular Cover Problem with Lower Adaptive Complexity

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Titel: Efficient Parallel Algorithm for Minimum Cost Submodular Cover Problem with Lower Adaptive Complexity
Autoren: Hue T. Nguyen, Dung T. K. Ha, Canh V. Pham
Quelle: Asia-Pacific Journal of Operational Research. 41
Verlagsinformationen: World Scientific Pub Co Pte Ltd, 2024.
Publikationsjahr: 2024
Schlagwörter: 0211 other engineering and technologies, 02 engineering and technology
Beschreibung: In this paper, we study the Minimum Cost Submodular Cover ([Formula: see text]) problem over the ground set of size [Formula: see text], which aims at finding a subset with the minimal cost required so that the utility submodular function exceeds a given threshold. The problem has recently attracted a lot of attention due to its applications in various domains of operations research and artificial intelligence. However, the existing algorithms for this problem may not be easy to parallelize because of their costly adaptive complexity. However, the existing algorithms for this problem may not be effectively parallelized because of their costly adaptive complexity. This paper proposes an efficient parallel algorithm that returns a [Formula: see text]-bicriteria approximation solution within [Formula: see text] adaptive complexity, where [Formula: see text] are fixed parameters. Our algorithm requires [Formula: see text] query complexity, however, it can reduce to [Formula: see text] instead while retaining a low adaptive complexity of [Formula: see text]. Therefore, our algorithm not only achieves the same approximation guarantees as the state of the art but also significantly improves the best-known low adaptive complexity algorithm for the above problem.
Publikationsart: Article
Sprache: English
ISSN: 1793-7019
0217-5959
DOI: 10.1142/s0217595924500052
Dokumentencode: edsair.doi...........539b46bf6f77aa67ece846f1e41c907c
Datenbank: OpenAIRE
Beschreibung
Abstract:In this paper, we study the Minimum Cost Submodular Cover ([Formula: see text]) problem over the ground set of size [Formula: see text], which aims at finding a subset with the minimal cost required so that the utility submodular function exceeds a given threshold. The problem has recently attracted a lot of attention due to its applications in various domains of operations research and artificial intelligence. However, the existing algorithms for this problem may not be easy to parallelize because of their costly adaptive complexity. However, the existing algorithms for this problem may not be effectively parallelized because of their costly adaptive complexity. This paper proposes an efficient parallel algorithm that returns a [Formula: see text]-bicriteria approximation solution within [Formula: see text] adaptive complexity, where [Formula: see text] are fixed parameters. Our algorithm requires [Formula: see text] query complexity, however, it can reduce to [Formula: see text] instead while retaining a low adaptive complexity of [Formula: see text]. Therefore, our algorithm not only achieves the same approximation guarantees as the state of the art but also significantly improves the best-known low adaptive complexity algorithm for the above problem.
ISSN:17937019
02175959
DOI:10.1142/s0217595924500052