A hybrid global optimization algorithm for non-linear least squares regression
Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excludin...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Žilinskas, Antanas [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2012 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer Science+Business Media, LLC. 2012 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Journal of global optimization - Springer US, 1991, 56(2012), 2 vom: 10. Jan., Seite 265-277 |
|---|---|
| Übergeordnetes Werk: |
volume:56 ; year:2012 ; number:2 ; day:10 ; month:01 ; pages:265-277 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10898-011-9840-9 |
|---|
| Katalog-ID: |
OLC2030644021 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2030644021 | ||
| 003 | DE-627 | ||
| 005 | 20230503141509.0 | ||
| 007 | tu | ||
| 008 | 200819s2012 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s10898-011-9840-9 |2 doi | |
| 035 | |a (DE-627)OLC2030644021 | ||
| 035 | |a (DE-He213)s10898-011-9840-9-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 510 |q VZ |
| 084 | |a 17,1 |2 ssgn | ||
| 084 | |a 83.00 |2 bkl | ||
| 100 | 1 | |a Žilinskas, Antanas |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a A hybrid global optimization algorithm for non-linear least squares regression |
| 264 | 1 | |c 2012 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer Science+Business Media, LLC. 2012 | ||
| 520 | |a Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. | ||
| 650 | 4 | |a Global optimization | |
| 650 | 4 | |a Simplicial partition | |
| 650 | 4 | |a Non-linear least squares | |
| 700 | 1 | |a Žilinskas, Julius |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of global optimization |d Springer US, 1991 |g 56(2012), 2 vom: 10. Jan., Seite 265-277 |w (DE-627)130979074 |w (DE-600)1074566-X |w (DE-576)034188533 |x 0925-5001 |7 nnns |
| 773 | 1 | 8 | |g volume:56 |g year:2012 |g number:2 |g day:10 |g month:01 |g pages:265-277 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s10898-011-9840-9 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a SSG-OLC-WIW | ||
| 912 | |a SSG-OPC-MAT | ||
| 912 | |a GBV_ILN_26 | ||
| 912 | |a GBV_ILN_32 | ||
| 912 | |a GBV_ILN_40 | ||
| 912 | |a GBV_ILN_65 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_215 | ||
| 912 | |a GBV_ILN_2006 | ||
| 912 | |a GBV_ILN_2012 | ||
| 912 | |a GBV_ILN_2030 | ||
| 912 | |a GBV_ILN_2088 | ||
| 912 | |a GBV_ILN_4266 | ||
| 912 | |a GBV_ILN_4311 | ||
| 936 | b | k | |a 83.00 |q VZ |
| 951 | |a AR | ||
| 952 | |d 56 |j 2012 |e 2 |b 10 |c 01 |h 265-277 | ||
| author_variant |
a ž až j ž jž |
|---|---|
| matchkey_str |
article:09255001:2012----::hbigoaotmztoagrtmonnieres |
| hierarchy_sort_str |
2012 |
| bklnumber |
83.00 |
| publishDate |
2012 |
| allfields |
10.1007/s10898-011-9840-9 doi (DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p DE-627 ger DE-627 rakwb eng 510 VZ 17,1 ssgn 83.00 bkl Žilinskas, Antanas verfasserin aut A hybrid global optimization algorithm for non-linear least squares regression 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC. 2012 Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Global optimization Simplicial partition Non-linear least squares Žilinskas, Julius aut Enthalten in Journal of global optimization Springer US, 1991 56(2012), 2 vom: 10. Jan., Seite 265-277 (DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 0925-5001 nnns volume:56 year:2012 number:2 day:10 month:01 pages:265-277 https://doi.org/10.1007/s10898-011-9840-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 83.00 VZ AR 56 2012 2 10 01 265-277 |
| spelling |
10.1007/s10898-011-9840-9 doi (DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p DE-627 ger DE-627 rakwb eng 510 VZ 17,1 ssgn 83.00 bkl Žilinskas, Antanas verfasserin aut A hybrid global optimization algorithm for non-linear least squares regression 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC. 2012 Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Global optimization Simplicial partition Non-linear least squares Žilinskas, Julius aut Enthalten in Journal of global optimization Springer US, 1991 56(2012), 2 vom: 10. Jan., Seite 265-277 (DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 0925-5001 nnns volume:56 year:2012 number:2 day:10 month:01 pages:265-277 https://doi.org/10.1007/s10898-011-9840-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 83.00 VZ AR 56 2012 2 10 01 265-277 |
| allfields_unstemmed |
10.1007/s10898-011-9840-9 doi (DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p DE-627 ger DE-627 rakwb eng 510 VZ 17,1 ssgn 83.00 bkl Žilinskas, Antanas verfasserin aut A hybrid global optimization algorithm for non-linear least squares regression 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC. 2012 Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Global optimization Simplicial partition Non-linear least squares Žilinskas, Julius aut Enthalten in Journal of global optimization Springer US, 1991 56(2012), 2 vom: 10. Jan., Seite 265-277 (DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 0925-5001 nnns volume:56 year:2012 number:2 day:10 month:01 pages:265-277 https://doi.org/10.1007/s10898-011-9840-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 83.00 VZ AR 56 2012 2 10 01 265-277 |
| allfieldsGer |
10.1007/s10898-011-9840-9 doi (DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p DE-627 ger DE-627 rakwb eng 510 VZ 17,1 ssgn 83.00 bkl Žilinskas, Antanas verfasserin aut A hybrid global optimization algorithm for non-linear least squares regression 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC. 2012 Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Global optimization Simplicial partition Non-linear least squares Žilinskas, Julius aut Enthalten in Journal of global optimization Springer US, 1991 56(2012), 2 vom: 10. Jan., Seite 265-277 (DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 0925-5001 nnns volume:56 year:2012 number:2 day:10 month:01 pages:265-277 https://doi.org/10.1007/s10898-011-9840-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 83.00 VZ AR 56 2012 2 10 01 265-277 |
| allfieldsSound |
10.1007/s10898-011-9840-9 doi (DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p DE-627 ger DE-627 rakwb eng 510 VZ 17,1 ssgn 83.00 bkl Žilinskas, Antanas verfasserin aut A hybrid global optimization algorithm for non-linear least squares regression 2012 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC. 2012 Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Global optimization Simplicial partition Non-linear least squares Žilinskas, Julius aut Enthalten in Journal of global optimization Springer US, 1991 56(2012), 2 vom: 10. Jan., Seite 265-277 (DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 0925-5001 nnns volume:56 year:2012 number:2 day:10 month:01 pages:265-277 https://doi.org/10.1007/s10898-011-9840-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 83.00 VZ AR 56 2012 2 10 01 265-277 |
| language |
English |
| source |
Enthalten in Journal of global optimization 56(2012), 2 vom: 10. Jan., Seite 265-277 volume:56 year:2012 number:2 day:10 month:01 pages:265-277 |
| sourceStr |
Enthalten in Journal of global optimization 56(2012), 2 vom: 10. Jan., Seite 265-277 volume:56 year:2012 number:2 day:10 month:01 pages:265-277 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Global optimization Simplicial partition Non-linear least squares |
| dewey-raw |
510 |
| isfreeaccess_bool |
false |
| container_title |
Journal of global optimization |
| authorswithroles_txt_mv |
Žilinskas, Antanas @@aut@@ Žilinskas, Julius @@aut@@ |
| publishDateDaySort_date |
2012-01-10T00:00:00Z |
| hierarchy_top_id |
130979074 |
| dewey-sort |
3510 |
| id |
OLC2030644021 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2030644021</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503141509.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2012 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10898-011-9840-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2030644021</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10898-011-9840-9-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">17,1</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">83.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Žilinskas, Antanas</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A hybrid global optimization algorithm for non-linear least squares regression</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC. 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Global optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simplicial partition</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Non-linear least squares</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Žilinskas, Julius</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of global optimization</subfield><subfield code="d">Springer US, 1991</subfield><subfield code="g">56(2012), 2 vom: 10. Jan., Seite 265-277</subfield><subfield code="w">(DE-627)130979074</subfield><subfield code="w">(DE-600)1074566-X</subfield><subfield code="w">(DE-576)034188533</subfield><subfield code="x">0925-5001</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:56</subfield><subfield code="g">year:2012</subfield><subfield code="g">number:2</subfield><subfield code="g">day:10</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:265-277</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10898-011-9840-9</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_215</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2030</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4266</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4311</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">83.00</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">56</subfield><subfield code="j">2012</subfield><subfield code="e">2</subfield><subfield code="b">10</subfield><subfield code="c">01</subfield><subfield code="h">265-277</subfield></datafield></record></collection>
|
| author |
Žilinskas, Antanas |
| spellingShingle |
Žilinskas, Antanas ddc 510 ssgn 17,1 bkl 83.00 misc Global optimization misc Simplicial partition misc Non-linear least squares A hybrid global optimization algorithm for non-linear least squares regression |
| authorStr |
Žilinskas, Antanas |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)130979074 |
| format |
Article |
| dewey-ones |
510 - Mathematics |
| delete_txt_mv |
keep |
| author_role |
aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0925-5001 |
| topic_title |
510 VZ 17,1 ssgn 83.00 bkl A hybrid global optimization algorithm for non-linear least squares regression Global optimization Simplicial partition Non-linear least squares |
| topic |
ddc 510 ssgn 17,1 bkl 83.00 misc Global optimization misc Simplicial partition misc Non-linear least squares |
| topic_unstemmed |
ddc 510 ssgn 17,1 bkl 83.00 misc Global optimization misc Simplicial partition misc Non-linear least squares |
| topic_browse |
ddc 510 ssgn 17,1 bkl 83.00 misc Global optimization misc Simplicial partition misc Non-linear least squares |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Journal of global optimization |
| hierarchy_parent_id |
130979074 |
| dewey-tens |
510 - Mathematics |
| hierarchy_top_title |
Journal of global optimization |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)130979074 (DE-600)1074566-X (DE-576)034188533 |
| title |
A hybrid global optimization algorithm for non-linear least squares regression |
| ctrlnum |
(DE-627)OLC2030644021 (DE-He213)s10898-011-9840-9-p |
| title_full |
A hybrid global optimization algorithm for non-linear least squares regression |
| author_sort |
Žilinskas, Antanas |
| journal |
Journal of global optimization |
| journalStr |
Journal of global optimization |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science |
| recordtype |
marc |
| publishDateSort |
2012 |
| contenttype_str_mv |
txt |
| container_start_page |
265 |
| author_browse |
Žilinskas, Antanas Žilinskas, Julius |
| container_volume |
56 |
| class |
510 VZ 17,1 ssgn 83.00 bkl |
| format_se |
Aufsätze |
| author-letter |
Žilinskas, Antanas |
| doi_str_mv |
10.1007/s10898-011-9840-9 |
| dewey-full |
510 |
| title_sort |
a hybrid global optimization algorithm for non-linear least squares regression |
| title_auth |
A hybrid global optimization algorithm for non-linear least squares regression |
| abstract |
Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. © Springer Science+Business Media, LLC. 2012 |
| abstractGer |
Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. © Springer Science+Business Media, LLC. 2012 |
| abstract_unstemmed |
Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. © Springer Science+Business Media, LLC. 2012 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_26 GBV_ILN_32 GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_215 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2030 GBV_ILN_2088 GBV_ILN_4266 GBV_ILN_4311 |
| container_issue |
2 |
| title_short |
A hybrid global optimization algorithm for non-linear least squares regression |
| url |
https://doi.org/10.1007/s10898-011-9840-9 |
| remote_bool |
false |
| author2 |
Žilinskas, Julius |
| author2Str |
Žilinskas, Julius |
| ppnlink |
130979074 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s10898-011-9840-9 |
| up_date |
2024-07-04T02:43:27.520Z |
| _version_ |
1803614691027582976 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2030644021</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503141509.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2012 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10898-011-9840-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2030644021</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10898-011-9840-9-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">17,1</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">83.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Žilinskas, Antanas</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A hybrid global optimization algorithm for non-linear least squares regression</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2012</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC. 2012</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Global optimization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simplicial partition</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Non-linear least squares</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Žilinskas, Julius</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of global optimization</subfield><subfield code="d">Springer US, 1991</subfield><subfield code="g">56(2012), 2 vom: 10. Jan., Seite 265-277</subfield><subfield code="w">(DE-627)130979074</subfield><subfield code="w">(DE-600)1074566-X</subfield><subfield code="w">(DE-576)034188533</subfield><subfield code="x">0925-5001</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:56</subfield><subfield code="g">year:2012</subfield><subfield code="g">number:2</subfield><subfield code="g">day:10</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:265-277</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10898-011-9840-9</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_32</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_215</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2030</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4266</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4311</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">83.00</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">56</subfield><subfield code="j">2012</subfield><subfield code="e">2</subfield><subfield code="b">10</subfield><subfield code="c">01</subfield><subfield code="h">265-277</subfield></datafield></record></collection>
|
| score |
7.3987494 |