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https://id.e-science.pl/records/78457Resource metadata
Title |
Probabilistic properties of threshold ang greedy algorithms for the binary knapsack problem (PN-1986-03) |
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Persons |
Authors:
Marek Sylwester Libura, Krzysztof Marcin Szkatuła
Partner: Systems Research Institute Polish Academy of Sciences, Warsaw |
Description |
In this paper the threshold algorithm for the binary knapsack problem is considered and its connections with well-known greedy algorithm is analyzed. Probabilistic analysis of the threshold algorithm in the asymptotic case (for large sizes of problems) is performed. It is known that for a given class of random knapsack problems and for any sizes n of a problem, a threshold value can be found such that the corresponding threshold solution is both a greedy and optimal solution of the knapsack problem with a slightly perturbed right-hand side of the constraint. The perturbation is asymptotically equal to zero, almost surely. (English) |
Keywords | "zachłanny algorytm"@pl, "binary knapsack problem"@en, "probabilistic properties"@en, "greedy algorithm"@en, "własności probabilistyczne"@pl, "binarny problem plecakowy"@pl |
Classification |
Resource type:
article, chapter Scientific discipline: Dziedzina nauk ścisłych i przyrodniczych / informatyka (2018) Destination group: pupils, students, scientists Harmful content: No |
Characteristics |
Title of source document: PN-1986-03
Place of publication: Warszawa Publisher: IBSPAN Time of publication: 1986 From page: 1 To page: 20 Resource language: English |
License | CC BY-SA 4.0 |
Technical information |
Submitter: Anna Wasilewska Availability date: 28-10-2022 |
Collections | Kolekcja Instytutu Badań Systemowych PAN w Warszawie |
Citation
Marek Sylwester Libura, Krzysztof Marcin Szkatuła. Probabilistic properties of threshold ang greedy algorithms for the binary knapsack problem (PN-1986-03). [article, chapter] Available in Atlas of Open Science Resources, . License: CC BY-SA 4.0, https://creativecommons.org/licenses/by-sa/4.0/legalcode.pl. Date of access: DD.MM.RRRR.
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