Stochastic simulation optimization: an optimal computing budget allocation
With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that a...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific Pub. Co.
c2011
|
| Schriftenreihe: | System engineering and operations research
v. 1 |
| Schlagworte: | |
| Online-Zugang: | FHN01 Volltext |
| Zusammenfassung: | With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation |
| Beschreibung: | xviii, 227 p. ill. (some col.) |
| ISBN: | 9789814282659 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV044637843 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 171120s2011 |||| o||u| ||||||eng d | ||
| 020 | |a 9789814282659 |c electronic bk. |9 978-981-4282-65-9 | ||
| 024 | 7 | |a 10.1142/7437 |2 doi | |
| 035 | |a (ZDB-124-WOP)00001050 | ||
| 035 | |a (OCoLC)839014708 | ||
| 035 | |a (DE-599)BVBBV044637843 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-92 | ||
| 082 | 0 | |a 620.00113 |2 22 | |
| 084 | |a SK 870 |0 (DE-625)143265: |2 rvk | ||
| 100 | 1 | |a Chen, Chun-hung |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Stochastic simulation optimization |b an optimal computing budget allocation |c Chun-Hung Chen, Loo Hay Lee |
| 264 | 1 | |a Singapore |b World Scientific Pub. Co. |c c2011 | |
| 300 | |a xviii, 227 p. |b ill. (some col.) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a System engineering and operations research |v v. 1 | |
| 520 | |a With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation | ||
| 650 | 4 | |a Systems engineering / Simulation methods | |
| 650 | 4 | |a Stochastic processes | |
| 650 | 4 | |a Mathematical optimization | |
| 650 | 0 | 7 | |a Stochastische Optimierung |0 (DE-588)4057625-5 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Stochastische optimale Kontrolle |0 (DE-588)4207850-7 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Stochastische Optimierung |0 (DE-588)4057625-5 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 689 | 1 | 0 | |a Stochastische optimale Kontrolle |0 (DE-588)4207850-7 |D s |
| 689 | 1 | |8 2\p |5 DE-604 | |
| 700 | 1 | |a Lee, Loo Hay |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9789814282642 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9814282642 |
| 856 | 4 | 0 | |u http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc |x Verlag |z URL des Erstveroeffentlichers |3 Volltext |
| 912 | |a ZDB-124-WOP | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030035816 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 883 | 1 | |8 2\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc |l FHN01 |p ZDB-124-WOP |q FHN_PDA_WOP |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804178053812715520 |
|---|---|
| any_adam_object | |
| author | Chen, Chun-hung |
| author_facet | Chen, Chun-hung |
| author_role | aut |
| author_sort | Chen, Chun-hung |
| author_variant | c h c chc |
| building | Verbundindex |
| bvnumber | BV044637843 |
| classification_rvk | SK 870 |
| collection | ZDB-124-WOP |
| ctrlnum | (ZDB-124-WOP)00001050 (OCoLC)839014708 (DE-599)BVBBV044637843 |
| dewey-full | 620.00113 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 620 - Engineering and allied operations |
| dewey-raw | 620.00113 |
| dewey-search | 620.00113 |
| dewey-sort | 3620.00113 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mathematik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03564nmm a2200529zcb4500</leader><controlfield tag="001">BV044637843</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">171120s2011 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789814282659</subfield><subfield code="c">electronic bk.</subfield><subfield code="9">978-981-4282-65-9</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1142/7437</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-124-WOP)00001050 </subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)839014708</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV044637843</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-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">620.00113</subfield><subfield code="2">22</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 870</subfield><subfield code="0">(DE-625)143265:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chen, Chun-hung</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Stochastic simulation optimization</subfield><subfield code="b">an optimal computing budget allocation</subfield><subfield code="c">Chun-Hung Chen, Loo Hay Lee</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Singapore</subfield><subfield code="b">World Scientific Pub. Co.</subfield><subfield code="c">c2011</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xviii, 227 p.</subfield><subfield code="b">ill. (some col.)</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">System engineering and operations research</subfield><subfield code="v">v. 1</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Systems engineering / Simulation methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stochastic processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical optimization</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Stochastische Optimierung</subfield><subfield code="0">(DE-588)4057625-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Stochastische optimale Kontrolle</subfield><subfield code="0">(DE-588)4207850-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Stochastische Optimierung</subfield><subfield code="0">(DE-588)4057625-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Stochastische optimale Kontrolle</subfield><subfield code="0">(DE-588)4207850-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="8">2\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lee, Loo Hay</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9789814282642</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9814282642</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveroeffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-124-WOP</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030035816</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">2\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-124-WOP</subfield><subfield code="q">FHN_PDA_WOP</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV044637843 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:57:52Z |
| institution | BVB |
| isbn | 9789814282659 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030035816 |
| oclc_num | 839014708 |
| open_access_boolean | |
| owner | DE-92 |
| owner_facet | DE-92 |
| physical | xviii, 227 p. ill. (some col.) |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | World Scientific Pub. Co. |
| record_format | marc |
| series2 | System engineering and operations research |
| spelling | Chen, Chun-hung Verfasser aut Stochastic simulation optimization an optimal computing budget allocation Chun-Hung Chen, Loo Hay Lee Singapore World Scientific Pub. Co. c2011 xviii, 227 p. ill. (some col.) txt rdacontent c rdamedia cr rdacarrier System engineering and operations research v. 1 With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation Systems engineering / Simulation methods Stochastic processes Mathematical optimization Stochastische Optimierung (DE-588)4057625-5 gnd rswk-swf Stochastische optimale Kontrolle (DE-588)4207850-7 gnd rswk-swf Stochastische Optimierung (DE-588)4057625-5 s 1\p DE-604 Stochastische optimale Kontrolle (DE-588)4207850-7 s 2\p DE-604 Lee, Loo Hay Sonstige oth Erscheint auch als Druck-Ausgabe 9789814282642 Erscheint auch als Druck-Ausgabe 9814282642 http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc Verlag URL des Erstveroeffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Chen, Chun-hung Stochastic simulation optimization an optimal computing budget allocation Systems engineering / Simulation methods Stochastic processes Mathematical optimization Stochastische Optimierung (DE-588)4057625-5 gnd Stochastische optimale Kontrolle (DE-588)4207850-7 gnd |
| subject_GND | (DE-588)4057625-5 (DE-588)4207850-7 |
| title | Stochastic simulation optimization an optimal computing budget allocation |
| title_auth | Stochastic simulation optimization an optimal computing budget allocation |
| title_exact_search | Stochastic simulation optimization an optimal computing budget allocation |
| title_full | Stochastic simulation optimization an optimal computing budget allocation Chun-Hung Chen, Loo Hay Lee |
| title_fullStr | Stochastic simulation optimization an optimal computing budget allocation Chun-Hung Chen, Loo Hay Lee |
| title_full_unstemmed | Stochastic simulation optimization an optimal computing budget allocation Chun-Hung Chen, Loo Hay Lee |
| title_short | Stochastic simulation optimization |
| title_sort | stochastic simulation optimization an optimal computing budget allocation |
| title_sub | an optimal computing budget allocation |
| topic | Systems engineering / Simulation methods Stochastic processes Mathematical optimization Stochastische Optimierung (DE-588)4057625-5 gnd Stochastische optimale Kontrolle (DE-588)4207850-7 gnd |
| topic_facet | Systems engineering / Simulation methods Stochastic processes Mathematical optimization Stochastische Optimierung Stochastische optimale Kontrolle |
| url | http://www.worldscientific.com/worldscibooks/10.1142/7437#t=toc |
| work_keys_str_mv | AT chenchunhung stochasticsimulationoptimizationanoptimalcomputingbudgetallocation AT leeloohay stochasticsimulationoptimizationanoptimalcomputingbudgetallocation |