Aggregation in Large-Scale Optimization:
Gespeichert in:
Beteilige Person: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | Englisch |
Veröffentlicht: |
Boston, MA
Springer US
2003
|
Schriftenreihe: | Applied Optimization
83 |
Schlagwörter: | |
Links: | https://doi.org/10.1007/978-1-4419-9154-6 |
Beschreibung: | When analyzing systems with a large number of parameters, the dimen sion of the original system may present insurmountable difficulties for the analysis. It may then be convenient to reformulate the original system in terms of substantially fewer aggregated variables, or macrovariables. In other words, an original system with an n-dimensional vector of states is reformulated as a system with a vector of dimension much less than n. The aggregated variables are either readily defined and processed, or the aggregated system may be considered as an approximate model for the orig inal system. In the latter case, the operation of the original system can be exhaustively analyzed within the framework of the aggregated model, and one faces the problems of defining the rules for introducing macrovariables, specifying loss of information and accuracy, recovering original variables from aggregates, etc. We consider also in detail the so-called iterative aggregation approach. It constructs an iterative process, at· every step of which a macroproblem is solved that is simpler than the original problem because of its lower dimension. Aggregation weights are then updated, and the procedure passes to the next step. Macrovariables are commonly used in coordinating problems of hierarchical optimization |
Umfang: | 1 Online-Ressource (XII, 291 p) |
ISBN: | 9781441991546 9781461348122 |
ISSN: | 1384-6485 |
DOI: | 10.1007/978-1-4419-9154-6 |
Internformat
MARC
LEADER | 00000nam a2200000zcb4500 | ||
---|---|---|---|
001 | BV042419318 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
007 | cr|uuu---uuuuu | ||
008 | 150317s2003 xx o|||| 00||| eng d | ||
020 | |a 9781441991546 |c Online |9 978-1-4419-9154-6 | ||
020 | |a 9781461348122 |c Print |9 978-1-4613-4812-2 | ||
024 | 7 | |a 10.1007/978-1-4419-9154-6 |2 doi | |
035 | |a (OCoLC)864738549 | ||
035 | |a (DE-599)BVBBV042419318 | ||
040 | |a DE-604 |b ger |e aacr | ||
041 | 0 | |a eng | |
049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
082 | 0 | |a 519.6 |2 23 | |
084 | |a MAT 000 |2 stub | ||
100 | 1 | |a Litvinchev, Igor |e Verfasser |4 aut | |
245 | 1 | 0 | |a Aggregation in Large-Scale Optimization |c by Igor Litvinchev, Vladimir Tsurkov |
264 | 1 | |a Boston, MA |b Springer US |c 2003 | |
300 | |a 1 Online-Ressource (XII, 291 p) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
490 | 0 | |a Applied Optimization |v 83 |x 1384-6485 | |
500 | |a When analyzing systems with a large number of parameters, the dimen sion of the original system may present insurmountable difficulties for the analysis. It may then be convenient to reformulate the original system in terms of substantially fewer aggregated variables, or macrovariables. In other words, an original system with an n-dimensional vector of states is reformulated as a system with a vector of dimension much less than n. The aggregated variables are either readily defined and processed, or the aggregated system may be considered as an approximate model for the orig inal system. In the latter case, the operation of the original system can be exhaustively analyzed within the framework of the aggregated model, and one faces the problems of defining the rules for introducing macrovariables, specifying loss of information and accuracy, recovering original variables from aggregates, etc. We consider also in detail the so-called iterative aggregation approach. It constructs an iterative process, at· every step of which a macroproblem is solved that is simpler than the original problem because of its lower dimension. Aggregation weights are then updated, and the procedure passes to the next step. Macrovariables are commonly used in coordinating problems of hierarchical optimization | ||
650 | 4 | |a Mathematics | |
650 | 4 | |a Systems theory | |
650 | 4 | |a Mathematical optimization | |
650 | 4 | |a Optimization | |
650 | 4 | |a Calculus of Variations and Optimal Control; Optimization | |
650 | 4 | |a Systems Theory, Control | |
650 | 4 | |a Mathematical Modeling and Industrial Mathematics | |
650 | 4 | |a Mathematik | |
700 | 1 | |a Tsurkov, Vladimir |e Sonstige |4 oth | |
856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4419-9154-6 |x Verlag |3 Volltext |
912 | |a ZDB-2-SMA | ||
912 | |a ZDB-2-BAE | ||
940 | 1 | |q ZDB-2-SMA_Archive | |
943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-027854735 |
Datensatz im Suchindex
DE-BY-TUM_katkey | 2066327 |
---|---|
_version_ | 1821931179707727873 |
any_adam_object | |
author | Litvinchev, Igor |
author_facet | Litvinchev, Igor |
author_role | aut |
author_sort | Litvinchev, Igor |
author_variant | i l il |
building | Verbundindex |
bvnumber | BV042419318 |
classification_tum | MAT 000 |
collection | ZDB-2-SMA ZDB-2-BAE |
ctrlnum | (OCoLC)864738549 (DE-599)BVBBV042419318 |
dewey-full | 519.6 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.6 |
dewey-search | 519.6 |
dewey-sort | 3519.6 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
doi_str_mv | 10.1007/978-1-4419-9154-6 |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02871nam a2200481zcb4500</leader><controlfield tag="001">BV042419318</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s2003 xx o|||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781441991546</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4419-9154-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781461348122</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-4613-4812-2</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4419-9154-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)864738549</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042419318</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.6</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Litvinchev, Igor</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Aggregation in Large-Scale Optimization</subfield><subfield code="c">by Igor Litvinchev, Vladimir Tsurkov</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boston, MA</subfield><subfield code="b">Springer US</subfield><subfield code="c">2003</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XII, 291 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Applied Optimization</subfield><subfield code="v">83</subfield><subfield code="x">1384-6485</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">When analyzing systems with a large number of parameters, the dimen sion of the original system may present insurmountable difficulties for the analysis. It may then be convenient to reformulate the original system in terms of substantially fewer aggregated variables, or macrovariables. In other words, an original system with an n-dimensional vector of states is reformulated as a system with a vector of dimension much less than n. The aggregated variables are either readily defined and processed, or the aggregated system may be considered as an approximate model for the orig inal system. In the latter case, the operation of the original system can be exhaustively analyzed within the framework of the aggregated model, and one faces the problems of defining the rules for introducing macrovariables, specifying loss of information and accuracy, recovering original variables from aggregates, etc. We consider also in detail the so-called iterative aggregation approach. It constructs an iterative process, at· every step of which a macroproblem is solved that is simpler than the original problem because of its lower dimension. Aggregation weights are then updated, and the procedure passes to the next step. Macrovariables are commonly used in coordinating problems of hierarchical optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Systems theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Calculus of Variations and Optimal Control; Optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Systems Theory, Control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical Modeling and Industrial Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tsurkov, Vladimir</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4419-9154-6</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027854735</subfield></datafield></record></collection> |
id | DE-604.BV042419318 |
illustrated | Not Illustrated |
indexdate | 2024-12-20T17:10:40Z |
institution | BVB |
isbn | 9781441991546 9781461348122 |
issn | 1384-6485 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027854735 |
oclc_num | 864738549 |
open_access_boolean | |
owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
physical | 1 Online-Ressource (XII, 291 p) |
psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
publishDate | 2003 |
publishDateSearch | 2003 |
publishDateSort | 2003 |
publisher | Springer US |
record_format | marc |
series2 | Applied Optimization |
spellingShingle | Litvinchev, Igor Aggregation in Large-Scale Optimization Mathematics Systems theory Mathematical optimization Optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Mathematical Modeling and Industrial Mathematics Mathematik |
title | Aggregation in Large-Scale Optimization |
title_auth | Aggregation in Large-Scale Optimization |
title_exact_search | Aggregation in Large-Scale Optimization |
title_full | Aggregation in Large-Scale Optimization by Igor Litvinchev, Vladimir Tsurkov |
title_fullStr | Aggregation in Large-Scale Optimization by Igor Litvinchev, Vladimir Tsurkov |
title_full_unstemmed | Aggregation in Large-Scale Optimization by Igor Litvinchev, Vladimir Tsurkov |
title_short | Aggregation in Large-Scale Optimization |
title_sort | aggregation in large scale optimization |
topic | Mathematics Systems theory Mathematical optimization Optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Mathematical Modeling and Industrial Mathematics Mathematik |
topic_facet | Mathematics Systems theory Mathematical optimization Optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Mathematical Modeling and Industrial Mathematics Mathematik |
url | https://doi.org/10.1007/978-1-4419-9154-6 |
work_keys_str_mv | AT litvinchevigor aggregationinlargescaleoptimization AT tsurkovvladimir aggregationinlargescaleoptimization |