Harrison Kyle Robert (25 results)

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  • Language: English

    Published by Cham, Springer International Publishing : Imprint: Springer., 2022

    3030883140 / 9783030883140

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    Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, GermanyUniversitätsbuchhandlung Herta Hold GmbH

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    1st ed. 2022. VIII, 214 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Adaptation, Learning, and Optimization, 26. Sprache: Englisch.

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  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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    Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

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  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

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    Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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    Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

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    Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

    • Softcover

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    Taschenbuch. Condition: Neu. Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling | Kyle Robert Harrison (u. a.) | Taschenbuch | Adaptation, Learning, and Optimization | viii | Englisch | 2022 | Springer | EAN 9783030883171 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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    Paperback. Condition: Brand New. 222 pages. 9.25x6.10x0.47 inches. In Stock.

  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

    • Softcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.

  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

    • Hardcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.

  • Published by The Crowell-Collier Publishing Company, USA, 1948

    • Softcover
    • First Edition

    Seller: RareNonFiction, IOBA, Ladysmith, BC, CanadaRareNonFiction, IOBA

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    Single Issue Magazine. Condition: Good. First Edition. 78 pages. Articles: Traffic Traps for Tourists - unjust arrests in many parts of the U.S.; Red Clouds over Olympus - Life in Greek village of Magoula is miserable under the Communists; The Secret Papers of Harry L. Hopkins (part 13) - from Cairo to Teheran - the first meeting with Stalin.Sunday Dinner - lady in the kitchen; Pot Shots by One Shot Ross - Boxing Manager Wirt Ross; "There Goes Rusty" - one of the world's fastest greyhounds. Fiction: Plenty of Time for Love; The Inspector had a Wife; The Fugitive; The Logger and the Lady; River Crossing; An Affair of State (part 3 of 4). Ads include: Studebaker cars; Vitalis (with Bob Feller); Philco radio-phonographs; Firestone "Super-Balloon" tires; Gillette Blue Blades (2-pages in color); Kaiser-Frazer cars (centerfold); Pllymouth; "Good Sam" movie with Gary Cooper; Schlitz beer; GM Electro-motive division; Coke - shows Coke machine at gas station; Texaco - shows young lady water skiing; Rice-Stix; U.S. Army; Lucky Strike cigarettes (back cover). Unmarked with moderate wear and minor bits of moisture exposure to top and bottom edges. A sound vintage copy. Patterson, Robert; Holland, Robert P.; Mitchell, Michael; Pike, John; Ketcham, Hank; Gabriele, Al; Dawes, Edwin; La Salle, Charles; Wolsky, Milton; (illustrator).

  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

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  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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  • Language: English

    Published by Springer International Publishing Nov 2021, 2021

    3030883140 / 9783030883140

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing. 224 pp. Englisch.

  • Language: English

    Published by Springer International Publishing Nov 2022, 2022

    3030883175 / 9783030883171

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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing. 224 pp. Englisch.

  • Language: English

    Published by Springer, Berlin|Springer International Publishing|Springer, 2021

    3030883140 / 9783030883140

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    Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains..

  • Language: English

    Published by Springer, Berlin|Springer International Publishing|Springer, 2022

    3030883175 / 9783030883171

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains..

  • Language: English

    Published by Springer, 2022

    3030883175 / 9783030883171

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  • Language: English

    Published by Springer, 2021

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  • Language: English

    Published by Springer International Publishing, Springer International Publishing Nov 2021, 2021

    3030883140 / 9783030883140

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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes.This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 224 pp. Englisch.

  • Language: English

    Published by Springer International Publishing, Springer International Publishing Nov 2022, 2022

    3030883175 / 9783030883171

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes.This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 224 pp. Englisch.

  • Language: English

    Published by Springer, 2021

    3030883140 / 9783030883140

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