Robust Discrete Optimization and Its Applications:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boston, MA
Springer US
1997
|
| Series: | Nonconvex Optimization and Its Applications
14 |
| Subjects: | |
| Online Access: | Volltext |
| Item Description: | This book deals with decision making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness approach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; - It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; - It accounts for the risk averse nature of decision makers; and - It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of operational decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making |
| Physical Description: | 1 Online-Ressource (XVI, 358 p) |
| ISBN: | 9781475726206 9781441947642 |
| ISSN: | 1571-568X |
| DOI: | 10.1007/978-1-4757-2620-6 |
Staff View
MARC
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| 500 | |a This book deals with decision making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness approach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; - It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; - It accounts for the risk averse nature of decision makers; and - It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of operational decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making | ||
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| author | Kouvelis, Panos |
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| dewey-full | 519.6 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-2620-6 |
| format | Electronic eBook |
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| id | DE-604.BV042421365 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:08Z |
| institution | BVB |
| isbn | 9781475726206 9781441947642 |
| issn | 1571-568X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856782 |
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| physical | 1 Online-Ressource (XVI, 358 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 1997 |
| publishDateSearch | 1997 |
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| publisher | Springer US |
| record_format | marc |
| series | Nonconvex Optimization and Its Applications |
| series2 | Nonconvex Optimization and Its Applications |
| spelling | Kouvelis, Panos Verfasser aut Robust Discrete Optimization and Its Applications by Panos Kouvelis, Gang Yu Boston, MA Springer US 1997 1 Online-Ressource (XVI, 358 p) txt rdacontent c rdamedia cr rdacarrier Nonconvex Optimization and Its Applications 14 1571-568X This book deals with decision making in environments of significant data uncertainty, with particular emphasis on operations and production management applications. For such environments, we suggest the use of the robustness approach to decision making, which assumes inadequate knowledge of the decision maker about the random state of nature and develops a decision that hedges against the worst contingency that may arise. The main motivating factors for a decision maker to use the robustness approach are: - It does not ignore uncertainty and takes a proactive step in response to the fact that forecasted values of uncertain parameters will not occur in most environments; - It applies to decisions of unique, non-repetitive nature, which are common in many fast and dynamically changing environments; - It accounts for the risk averse nature of decision makers; and - It recognizes that even though decision environments are fraught with data uncertainties, decisions are evaluated ex post with the realized data. For all of the above reasons, robust decisions are dear to the heart of operational decision makers. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments. Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making Mathematics Algorithms Mathematical optimization Operations research Optimization Operation Research/Decision Theory Production/Logistics/Supply Chain Management Mathematik Diskrete Optimierung (DE-588)4150179-2 gnd rswk-swf Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd rswk-swf Diskrete Optimierung (DE-588)4150179-2 s Entscheidung bei Unsicherheit (DE-588)4070864-0 s 1\p DE-604 Yu, Gang Sonstige oth Nonconvex Optimization and Its Applications 14 (DE-604)BV010085908 14 https://doi.org/10.1007/978-1-4757-2620-6 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kouvelis, Panos Robust Discrete Optimization and Its Applications Nonconvex Optimization and Its Applications Mathematics Algorithms Mathematical optimization Operations research Optimization Operation Research/Decision Theory Production/Logistics/Supply Chain Management Mathematik Diskrete Optimierung (DE-588)4150179-2 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd |
| subject_GND | (DE-588)4150179-2 (DE-588)4070864-0 |
| title | Robust Discrete Optimization and Its Applications |
| title_auth | Robust Discrete Optimization and Its Applications |
| title_exact_search | Robust Discrete Optimization and Its Applications |
| title_full | Robust Discrete Optimization and Its Applications by Panos Kouvelis, Gang Yu |
| title_fullStr | Robust Discrete Optimization and Its Applications by Panos Kouvelis, Gang Yu |
| title_full_unstemmed | Robust Discrete Optimization and Its Applications by Panos Kouvelis, Gang Yu |
| title_short | Robust Discrete Optimization and Its Applications |
| title_sort | robust discrete optimization and its applications |
| topic | Mathematics Algorithms Mathematical optimization Operations research Optimization Operation Research/Decision Theory Production/Logistics/Supply Chain Management Mathematik Diskrete Optimierung (DE-588)4150179-2 gnd Entscheidung bei Unsicherheit (DE-588)4070864-0 gnd |
| topic_facet | Mathematics Algorithms Mathematical optimization Operations research Optimization Operation Research/Decision Theory Production/Logistics/Supply Chain Management Mathematik Diskrete Optimierung Entscheidung bei Unsicherheit |
| url | https://doi.org/10.1007/978-1-4757-2620-6 |
| volume_link | (DE-604)BV010085908 |
| work_keys_str_mv | AT kouvelispanos robustdiscreteoptimizationanditsapplications AT yugang robustdiscreteoptimizationanditsapplications |