Advances in Sensitivity Analysis and Parametric Programming:
The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to defi...
Gespeichert in:
Weitere Verfasser: | , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
New York, NY
Springer US
1997
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Ausgabe: | 1st ed. 1997 |
Schriftenreihe: | International Series in Operations Research & Management Science
6 |
Schlagworte: | |
Online-Zugang: | BTU01 URL des Erstveröffentlichers |
Zusammenfassung: | The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to define OR/MS are usually presented in terms of one subfield or the other. This separation comes about somewhat artificially: academic courses are conveniently subdivided with respect to prerequisites; an initial overview of OR/MS can be presented without requiring knowledge of probability and statistics; text books are conveniently divided into two related semester courses, with deterministic models coming first; academics tend to specialize in one subfield or the other; and practitioners also tend to be expert in a single subfield. But, no matter who is involved in an OR/MS modeling situation (deterministic or probabilistic - academic or practitioner), it is clear that a proper and correct treatment of any problem situation is accomplished only when the analysis cuts across this dichotomy |
Beschreibung: | 1 Online-Ressource (XXIII, 581 p) |
ISBN: | 9781461561033 |
DOI: | 10.1007/978-1-4615-6103-3 |
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520 | |a The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to define OR/MS are usually presented in terms of one subfield or the other. This separation comes about somewhat artificially: academic courses are conveniently subdivided with respect to prerequisites; an initial overview of OR/MS can be presented without requiring knowledge of probability and statistics; text books are conveniently divided into two related semester courses, with deterministic models coming first; academics tend to specialize in one subfield or the other; and practitioners also tend to be expert in a single subfield. But, no matter who is involved in an OR/MS modeling situation (deterministic or probabilistic - academic or practitioner), it is clear that a proper and correct treatment of any problem situation is accomplished only when the analysis cuts across this dichotomy | ||
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dewey-full | 658.40301 |
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dewey-ones | 658 - General management |
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discipline | Wirtschaftswissenschaften |
discipline_str_mv | Wirtschaftswissenschaften |
doi_str_mv | 10.1007/978-1-4615-6103-3 |
edition | 1st ed. 1997 |
format | Electronic eBook |
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series2 | International Series in Operations Research & Management Science |
spelling | Advances in Sensitivity Analysis and Parametric Programming edited by Tomas Gal, H.J. Greenberg 1st ed. 1997 New York, NY Springer US 1997 1 Online-Ressource (XXIII, 581 p) txt rdacontent c rdamedia cr rdacarrier International Series in Operations Research & Management Science 6 The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to define OR/MS are usually presented in terms of one subfield or the other. This separation comes about somewhat artificially: academic courses are conveniently subdivided with respect to prerequisites; an initial overview of OR/MS can be presented without requiring knowledge of probability and statistics; text books are conveniently divided into two related semester courses, with deterministic models coming first; academics tend to specialize in one subfield or the other; and practitioners also tend to be expert in a single subfield. But, no matter who is involved in an OR/MS modeling situation (deterministic or probabilistic - academic or practitioner), it is clear that a proper and correct treatment of any problem situation is accomplished only when the analysis cuts across this dichotomy Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Manufacturing, Machines, Tools, Processes Operations research Decision making Calculus of variations Manufactures Parametrische Optimierung (DE-588)4044615-3 gnd rswk-swf Sensitivitätsanalyse (DE-588)4129730-1 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Sensitivitätsanalyse (DE-588)4129730-1 s Parametrische Optimierung (DE-588)4044615-3 s DE-604 Gal, Tomas edt Greenberg, H.J. edt Erscheint auch als Druck-Ausgabe 9780792399179 Erscheint auch als Druck-Ausgabe 9781461377962 Erscheint auch als Druck-Ausgabe 9781461561040 https://doi.org/10.1007/978-1-4615-6103-3 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Advances in Sensitivity Analysis and Parametric Programming Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Manufacturing, Machines, Tools, Processes Operations research Decision making Calculus of variations Manufactures Parametrische Optimierung (DE-588)4044615-3 gnd Sensitivitätsanalyse (DE-588)4129730-1 gnd |
subject_GND | (DE-588)4044615-3 (DE-588)4129730-1 (DE-588)4143413-4 |
title | Advances in Sensitivity Analysis and Parametric Programming |
title_auth | Advances in Sensitivity Analysis and Parametric Programming |
title_exact_search | Advances in Sensitivity Analysis and Parametric Programming |
title_exact_search_txtP | Advances in Sensitivity Analysis and Parametric Programming |
title_full | Advances in Sensitivity Analysis and Parametric Programming edited by Tomas Gal, H.J. Greenberg |
title_fullStr | Advances in Sensitivity Analysis and Parametric Programming edited by Tomas Gal, H.J. Greenberg |
title_full_unstemmed | Advances in Sensitivity Analysis and Parametric Programming edited by Tomas Gal, H.J. Greenberg |
title_short | Advances in Sensitivity Analysis and Parametric Programming |
title_sort | advances in sensitivity analysis and parametric programming |
topic | Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Manufacturing, Machines, Tools, Processes Operations research Decision making Calculus of variations Manufactures Parametrische Optimierung (DE-588)4044615-3 gnd Sensitivitätsanalyse (DE-588)4129730-1 gnd |
topic_facet | Operations Research/Decision Theory Calculus of Variations and Optimal Control; Optimization Manufacturing, Machines, Tools, Processes Operations research Decision making Calculus of variations Manufactures Parametrische Optimierung Sensitivitätsanalyse Aufsatzsammlung |
url | https://doi.org/10.1007/978-1-4615-6103-3 |
work_keys_str_mv | AT galtomas advancesinsensitivityanalysisandparametricprogramming AT greenberghj advancesinsensitivityanalysisandparametricprogramming |