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100%: Silvia Luraghi: Stochastic Project Networks : Temporal Analysis, Scheduling and Cost Minimization (ISBN: 9783642615153) 1983, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
78%: Klaus Neumann: Stochastic Project Networks (ISBN: 9783540526643) in Englisch, Band: 344.Nur diese Ausgabe anzeigen…
Stochastic Project Networks : Temporal Analysis, Scheduling and Cost Minimization
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| Preise | 2018 | 2019 | 2023 |
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| Schnitt | Fr. 58.08 (€ 59.34)¹ | Fr. 54.84 (€ 56.03)¹ | Fr. 6.84 (€ 6.99)¹ |
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1
Stochastic Project Networks (1983)
~EN PB NWISBN: 9783540526643 bzw. 3540526641, vermutlich in Englisch, Springer Nature, Taschenbuch, neu.
Lieferung aus: Deutschland, Lagernd, zzgl. Versandkosten.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. Soft cover.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. Soft cover.
2
Stochastic Project Networks
DE PB NWISBN: 9783540526643 bzw. 3540526641, in Deutsch, Springer, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
buecher.de GmbH & Co. KG, [1].
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective.XI,237 pages - 242 x 170 mmVersandfertig in 3-5 Tagen, Softcover.
buecher.de GmbH & Co. KG, [1].
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective.XI,237 pages - 242 x 170 mmVersandfertig in 3-5 Tagen, Softcover.
3
Stochastic Project Networks (1983)
~EN NW EB DLISBN: 9783642615153 bzw. 3642615155, vermutlich in Englisch, Springer Shop, neu, E-Book, elektronischer Download.
Lieferung aus: Mexiko, Lagernd, zzgl. Versandkosten.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. eBook.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. eBook.
4
Stochastic Project Networks - Temporal Analysis, Scheduling and Cost Minimization (1983)
~EN NW EB DLISBN: 9783642615153 bzw. 3642615155, vermutlich in Englisch, Springer Berlin Heidelberg, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, Versandkostenfrei.
Stochastic Project Networks: Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "e classical"e project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. Englisch, Ebook.
Stochastic Project Networks: Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "e classical"e project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective. Englisch, Ebook.
5
Stochastic Project Networks: Temporal Analysis, Scheduling and Cost Minimization (Lecture Notes in Economics and Mathematical Systems)
DE PB NWISBN: 9783540526643 bzw. 3540526641, in Deutsch, Springer, Berlin/Heidelberg, Deutschland, Taschenbuch, neu.
Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
This item is printed on demand. Paperback. This book presents the state of the art of temporal analysis and cost minimization of projects, as well as project planning under limited resources where the projects are modelled by GERT networks. These projects are characterized by a stochastic evolution structure and possible feedback. The temporal analysis exploits the fact that Markov renewal processes can be associated with so-called EOR networks (special GERT networks all of whose nodes have exclusive-or entrance). For single-machine min-sum and min-max scheduling problems with EOR precedence constraints, two polynomial algorithms are presented. General min-sum problems are solved by dynamic programming. The cost minimization of projects modeled by EOR networks leads to Markov renewal decision processes and can be reduced to a stochastic dynamic programming problem. Basic concepts from the theory of graphs and networks, Markov renewal processes, deterministic scheduling, and dynamic programming are summarized. This makes the book self-contained. This item ships from La Vergne,TN.
This item is printed on demand. Paperback. This book presents the state of the art of temporal analysis and cost minimization of projects, as well as project planning under limited resources where the projects are modelled by GERT networks. These projects are characterized by a stochastic evolution structure and possible feedback. The temporal analysis exploits the fact that Markov renewal processes can be associated with so-called EOR networks (special GERT networks all of whose nodes have exclusive-or entrance). For single-machine min-sum and min-max scheduling problems with EOR precedence constraints, two polynomial algorithms are presented. General min-sum problems are solved by dynamic programming. The cost minimization of projects modeled by EOR networks leads to Markov renewal decision processes and can be reduced to a stochastic dynamic programming problem. Basic concepts from the theory of graphs and networks, Markov renewal processes, deterministic scheduling, and dynamic programming are summarized. This makes the book self-contained. This item ships from La Vergne,TN.
6
Stochastic Project Networks: Temporal Analysis, Scheduling and Cost Minimization (Lecture Notes in Economics and Mathematical Systems)
DE PB USISBN: 9783540526643 bzw. 3540526641, in Deutsch, Springer, Taschenbuch, gebraucht.
Von Händler/Antiquariat, Crashing Rocks Books [55397785], Punta Gorda, FL, U.S.A.
3540526641 One USED BOOK in good condition | Normal wear to cover and spine | Corner edge wear | Inventory sticker present | Corners rubbed | No supplements included | Page markings/highlighting.
3540526641 One USED BOOK in good condition | Normal wear to cover and spine | Corner edge wear | Inventory sticker present | Corners rubbed | No supplements included | Page markings/highlighting.
7
Stochastic Project Networks. Temporal Analysis, Scheduling and Cost Minimization (1990)
DE PB USISBN: 9783540526643 bzw. 3540526641, in Deutsch, Springer, Taschenbuch, gebraucht.
Von Händler/Antiquariat, Herb Tandree Philosophy Books [17426], Stroud, United Kingdom.
Paperback, This listing is a new book, a title currently in-print which we order directly and immediately from the publisher.
Paperback, This listing is a new book, a title currently in-print which we order directly and immediately from the publisher.
8
Stochastic Project Networks: Temporal Analysis, Scheduling and Cost Minimization: Vol 344 (1990)
DE PB NWISBN: 9783540526643 bzw. 3540526641, Band: 344, in Deutsch, Springer, Taschenbuch, neu.
Von Händler/Antiquariat, Revaluation Books [2134736], Exeter, DEV, United Kingdom.
1990 edition. 248 pages. 9.30x6.40x0.70 inches. In Stock.
1990 edition. 248 pages. 9.30x6.40x0.70 inches. In Stock.
9
Stochastic Project Networks (1990)
DE HC NWISBN: 9783540526643 bzw. 3540526641, in Deutsch, Springer Berlin Heidelberg, gebundenes Buch, neu.
Lieferung aus: Deutschland, Versandkostenfrei, Shipping in 3 days.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
10
Stochastic Project Networks
DE NW EBISBN: 9783642615153 bzw. 3642615155, in Deutsch, Springer Nature, neu, E-Book.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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