Nurse Rostering is a complex problem which arises in everyday activities and health care system in modern hospitals. The Nurse Rostering Problem is a subclass of the personnel scheduling problems, and most of its instances are NP-hard. Even though solving the Nurse Rostering Problem has been interested field for research from many years, still the Nurse Rostering done by manually. Meta heuristics GA, have been proved to be very efficient in obtaining near-optimal solutions for a variety of hard combinatorial problems including the NRP. Heuristics Algorithm have shown excellent search abilities, but often lose their efficacy when applied to large and complex problems, Many optimization methods suffer from the curse of dimensionality, which shown that their performance deteriorates quickly as the dimensionality of the search space increases. Need to provide some degree of parallelism in traditional approach. Nowadays, GPGPUs are able to provide the necessary computational resources to tackle these high-dimensional problems maintaining a limited execution time and a high portability.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nurse Rostering is a complex problem which arises in everyday activities and health care system in modern hospitals. The Nurse Rostering Problem is a subclass of the personnel scheduling problems, and most of its instances are NP-hard. Even though solving the Nurse Rostering Problem has been interested field for research from many years, still the Nurse Rostering done by manually. Meta heuristics GA, have been proved to be very efficient in obtaining near-optimal solutions for a variety of hard combinatorial problems including the NRP. Heuristics Algorithm have shown excellent search abilities, but often lose their efficacy when applied to large and complex problems, Many optimization methods suffer from the curse of dimensionality, which shown that their performance deteriorates quickly as the dimensionality of the search space increases. Need to provide some degree of parallelism in traditional approach. Nowadays, GPGPUs are able to provide the necessary computational resources to tackle these high-dimensional problems maintaining a limited execution time and a high portability. 76 pp. Englisch. Codice articolo 9783659900365
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Da: Books Puddle, Woodside, NY, U.S.A.
Condizione: New. Codice articolo 26404101396
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 409052875
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nurse Rostering is a complex problem which arises in everyday activities and health care system in modern hospitals. The Nurse Rostering Problem is a subclass of the personnel scheduling problems, and most of its instances are NP-hard. Even though solving the Nurse Rostering Problem has been interested field for research from many years, still the Nurse Rostering done by manually. Meta heuristics GA, have been proved to be very efficient in obtaining near-optimal solutions for a variety of hard combinatorial problems including the NRP. Heuristics Algorithm have shown excellent search abilities, but often lose their efficacy when applied to large and complex problems, Many optimization methods suffer from the curse of dimensionality, which shown that their performance deteriorates quickly as the dimensionality of the search space increases. Need to provide some degree of parallelism in traditional approach. Nowadays, GPGPUs are able to provide the necessary computational resources to tackle these high-dimensional problems maintaining a limited execution time and a high portability. Codice articolo 9783659900365
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhandare NileshName of Author:- Mr. Nilesh Dilip Bhandare,Place:-Satara,Date of Birth:- 11/08/1989,Address :782/3 Shaniwar peth,Opp. Jivanjyoyt Hospita Satara MH India,Parent:- Mrs. Swati Dilip BhandareName of Co-Author:- Mr. Sandip . Codice articolo 158606513
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock. Codice articolo 3659900362
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nurse Rostering is a complex problem which arises in everyday activities and health care system in modern hospitals. The Nurse Rostering Problem is a subclass of the personnel scheduling problems, and most of its instances are NP-hard. Even though solving the Nurse Rostering Problem has been interested field for research from many years, still the Nurse Rostering done by manually. Meta heuristics GA, have been proved to be very efficient in obtaining near-optimal solutions for a variety of hard combinatorial problems including the NRP. Heuristics Algorithm have shown excellent search abilities, but often lose their efficacy when applied to large and complex problems, Many optimization methods suffer from the curse of dimensionality, which shown that their performance deteriorates quickly as the dimensionality of the search space increases. Need to provide some degree of parallelism in traditional approach. Nowadays, GPGPUs are able to provide the necessary computational resources to tackle these high-dimensional problems maintaining a limited execution time and a high portability.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. Codice articolo 9783659900365
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Parallel Genetic Algorithmic approach for solving NRP | Nilesh Bhandare (u. a.) | Taschenbuch | 76 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659900365 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 103657194
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