Lingua: Inglese
Editore: Cham, Springer International Publishing : Imprint: Springer., 2022
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
Prima edizione
EUR 19,00
Quantità: 4 disponibili
Aggiungi al carrello1st 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.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Prima edizione
Hardcover. Condizione: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 156,12
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 146,99
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Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 147,37
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Aggiungi al carrelloCondizione: New. In.
Da: California Books, Miami, FL, U.S.A.
EUR 192,40
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Nov 2022, 2022
ISBN 10: 3030883175 ISBN 13: 9783030883171
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. 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.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing Nov 2021, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. 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.
Lingua: Inglese
Editore: Springer International Publishing, 2022
ISBN 10: 3030883175 ISBN 13: 9783030883171
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 160,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer International Publishing, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 160,49
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: 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.
Da: Revaluation Books, Exeter, Regno Unito
EUR 226,09
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 222 pages. 9.25x6.10x0.47 inches. In Stock.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: AussieBookSeller, Truganina, VIC, Australia
Prima edizione
EUR 223,06
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: The Crowell-Collier Publishing Company, USA, 1948
Da: RareNonFiction, IOBA, Ladysmith, BC, Canada
Membro dell'associazione: IOBA
Prima edizione
EUR 218,64
Quantità: 1 disponibili
Aggiungi al carrelloSingle Issue Magazine. Condizione: Good. Patterson, Robert; Holland, Robert P.; Mitchell, Michael; Pike, John; Ketcham, Hank; Gabriele, Al; Dawes, Edwin; La Salle, Charles; Wolsky, Milton; (illustratore). 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.
Lingua: Inglese
Editore: Springer International Publishing Nov 2022, 2022
ISBN 10: 3030883175 ISBN 13: 9783030883171
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer International Publishing Nov 2021, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 160,49
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: 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.
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030883175 ISBN 13: 9783030883171
Da: moluna, Greven, Germania
EUR 136,16
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: 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,.
Lingua: Inglese
Editore: Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: moluna, Greven, Germania
EUR 136,16
Quantità: Più di 20 disponibili
Aggiungi al carrelloGebunden. Condizione: 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,.
Da: Majestic Books, Hounslow, Regno Unito
EUR 203,29
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer International Publishing, 2021
ISBN 10: 3030883140 ISBN 13: 9783030883140
Da: preigu, Osnabrück, Germania
EUR 141,20
Quantità: 5 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling | Kyle Robert Harrison (u. a.) | Buch | viii | Englisch | 2021 | Springer International Publishing | EAN 9783030883140 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer International Publishing, 2022
ISBN 10: 3030883175 ISBN 13: 9783030883171
Da: preigu, Osnabrück, Germania
EUR 141,20
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling | Kyle Robert Harrison (u. a.) | Taschenbuch | viii | Englisch | 2022 | Springer International Publishing | EAN 9783030883171 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.