Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality
Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic dif...
Ausführliche Beschreibung
Autor*in: |
Nguyen, Dang H. [verfasserIn] |
---|
Format: |
Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2018 |
---|
Schlagwörter: |
---|
Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2018 |
---|
Übergeordnetes Werk: |
Enthalten in: Applied mathematics & optimization - Springer US, 1974, 81(2018), 2 vom: 28. Mai, Seite 443-478 |
---|---|
Übergeordnetes Werk: |
volume:81 ; year:2018 ; number:2 ; day:28 ; month:05 ; pages:443-478 |
Links: |
---|
DOI / URN: |
10.1007/s00245-018-9504-y |
---|
Katalog-ID: |
OLC2072646251 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | OLC2072646251 | ||
003 | DE-627 | ||
005 | 20230504131534.0 | ||
007 | tu | ||
008 | 200820s2018 xx ||||| 00| ||eng c | ||
024 | 7 | |a 10.1007/s00245-018-9504-y |2 doi | |
035 | |a (DE-627)OLC2072646251 | ||
035 | |a (DE-He213)s00245-018-9504-y-p | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 510 |q VZ |
100 | 1 | |a Nguyen, Dang H. |e verfasserin |4 aut | |
245 | 1 | 0 | |a Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
264 | 1 | |c 2018 | |
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, part of Springer Nature 2018 | ||
520 | |a Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. | ||
650 | 4 | |a Sustainability | |
650 | 4 | |a Near-optimal strategy | |
650 | 4 | |a Harvesting policy | |
650 | 4 | |a Long-run-average control | |
650 | 4 | |a Ergodicity | |
700 | 1 | |a Yin, George |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Applied mathematics & optimization |d Springer US, 1974 |g 81(2018), 2 vom: 28. Mai, Seite 443-478 |w (DE-627)129095184 |w (DE-600)7418-4 |w (DE-576)014431300 |x 0095-4616 |7 nnns |
773 | 1 | 8 | |g volume:81 |g year:2018 |g number:2 |g day:28 |g month:05 |g pages:443-478 |
856 | 4 | 1 | |u https://doi.org/10.1007/s00245-018-9504-y |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-OPC-MAT | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_2018 | ||
912 | |a GBV_ILN_4027 | ||
912 | |a GBV_ILN_4323 | ||
951 | |a AR | ||
952 | |d 81 |j 2018 |e 2 |b 28 |c 05 |h 443-478 |
author_variant |
d h n dh dhn g y gy |
---|---|
matchkey_str |
article:00954616:2018----::utialhretnplceudroguaeaer |
hierarchy_sort_str |
2018 |
publishDate |
2018 |
allfields |
10.1007/s00245-018-9504-y doi (DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p DE-627 ger DE-627 rakwb eng 510 VZ Nguyen, Dang H. verfasserin aut Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity Yin, George aut Enthalten in Applied mathematics & optimization Springer US, 1974 81(2018), 2 vom: 28. Mai, Seite 443-478 (DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 0095-4616 nnns volume:81 year:2018 number:2 day:28 month:05 pages:443-478 https://doi.org/10.1007/s00245-018-9504-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 AR 81 2018 2 28 05 443-478 |
spelling |
10.1007/s00245-018-9504-y doi (DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p DE-627 ger DE-627 rakwb eng 510 VZ Nguyen, Dang H. verfasserin aut Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity Yin, George aut Enthalten in Applied mathematics & optimization Springer US, 1974 81(2018), 2 vom: 28. Mai, Seite 443-478 (DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 0095-4616 nnns volume:81 year:2018 number:2 day:28 month:05 pages:443-478 https://doi.org/10.1007/s00245-018-9504-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 AR 81 2018 2 28 05 443-478 |
allfields_unstemmed |
10.1007/s00245-018-9504-y doi (DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p DE-627 ger DE-627 rakwb eng 510 VZ Nguyen, Dang H. verfasserin aut Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity Yin, George aut Enthalten in Applied mathematics & optimization Springer US, 1974 81(2018), 2 vom: 28. Mai, Seite 443-478 (DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 0095-4616 nnns volume:81 year:2018 number:2 day:28 month:05 pages:443-478 https://doi.org/10.1007/s00245-018-9504-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 AR 81 2018 2 28 05 443-478 |
allfieldsGer |
10.1007/s00245-018-9504-y doi (DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p DE-627 ger DE-627 rakwb eng 510 VZ Nguyen, Dang H. verfasserin aut Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity Yin, George aut Enthalten in Applied mathematics & optimization Springer US, 1974 81(2018), 2 vom: 28. Mai, Seite 443-478 (DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 0095-4616 nnns volume:81 year:2018 number:2 day:28 month:05 pages:443-478 https://doi.org/10.1007/s00245-018-9504-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 AR 81 2018 2 28 05 443-478 |
allfieldsSound |
10.1007/s00245-018-9504-y doi (DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p DE-627 ger DE-627 rakwb eng 510 VZ Nguyen, Dang H. verfasserin aut Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity Yin, George aut Enthalten in Applied mathematics & optimization Springer US, 1974 81(2018), 2 vom: 28. Mai, Seite 443-478 (DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 0095-4616 nnns volume:81 year:2018 number:2 day:28 month:05 pages:443-478 https://doi.org/10.1007/s00245-018-9504-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 AR 81 2018 2 28 05 443-478 |
language |
English |
source |
Enthalten in Applied mathematics & optimization 81(2018), 2 vom: 28. Mai, Seite 443-478 volume:81 year:2018 number:2 day:28 month:05 pages:443-478 |
sourceStr |
Enthalten in Applied mathematics & optimization 81(2018), 2 vom: 28. Mai, Seite 443-478 volume:81 year:2018 number:2 day:28 month:05 pages:443-478 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity |
dewey-raw |
510 |
isfreeaccess_bool |
false |
container_title |
Applied mathematics & optimization |
authorswithroles_txt_mv |
Nguyen, Dang H. @@aut@@ Yin, George @@aut@@ |
publishDateDaySort_date |
2018-05-28T00:00:00Z |
hierarchy_top_id |
129095184 |
dewey-sort |
3510 |
id |
OLC2072646251 |
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">OLC2072646251</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504131534.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2018 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00245-018-9504-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2072646251</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00245-018-9504-y-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="100" ind1="1" ind2=" "><subfield code="a">Nguyen, Dang H.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</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, part of Springer Nature 2018</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sustainability</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Near-optimal strategy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Harvesting policy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Long-run-average control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergodicity</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yin, George</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Applied mathematics & optimization</subfield><subfield code="d">Springer US, 1974</subfield><subfield code="g">81(2018), 2 vom: 28. Mai, Seite 443-478</subfield><subfield code="w">(DE-627)129095184</subfield><subfield code="w">(DE-600)7418-4</subfield><subfield code="w">(DE-576)014431300</subfield><subfield code="x">0095-4616</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2018</subfield><subfield code="g">number:2</subfield><subfield code="g">day:28</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:443-478</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00245-018-9504-y</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-OPC-MAT</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_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2018</subfield><subfield code="e">2</subfield><subfield code="b">28</subfield><subfield code="c">05</subfield><subfield code="h">443-478</subfield></datafield></record></collection>
|
author |
Nguyen, Dang H. |
spellingShingle |
Nguyen, Dang H. ddc 510 misc Sustainability misc Near-optimal strategy misc Harvesting policy misc Long-run-average control misc Ergodicity Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
authorStr |
Nguyen, Dang H. |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)129095184 |
format |
Article |
dewey-ones |
510 - Mathematics |
delete_txt_mv |
keep |
author_role |
aut aut |
collection |
OLC |
remote_str |
false |
illustrated |
Not Illustrated |
issn |
0095-4616 |
topic_title |
510 VZ Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality Sustainability Near-optimal strategy Harvesting policy Long-run-average control Ergodicity |
topic |
ddc 510 misc Sustainability misc Near-optimal strategy misc Harvesting policy misc Long-run-average control misc Ergodicity |
topic_unstemmed |
ddc 510 misc Sustainability misc Near-optimal strategy misc Harvesting policy misc Long-run-average control misc Ergodicity |
topic_browse |
ddc 510 misc Sustainability misc Near-optimal strategy misc Harvesting policy misc Long-run-average control misc Ergodicity |
format_facet |
Aufsätze Gedruckte Aufsätze |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
nc |
hierarchy_parent_title |
Applied mathematics & optimization |
hierarchy_parent_id |
129095184 |
dewey-tens |
510 - Mathematics |
hierarchy_top_title |
Applied mathematics & optimization |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)129095184 (DE-600)7418-4 (DE-576)014431300 |
title |
Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
ctrlnum |
(DE-627)OLC2072646251 (DE-He213)s00245-018-9504-y-p |
title_full |
Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
author_sort |
Nguyen, Dang H. |
journal |
Applied mathematics & optimization |
journalStr |
Applied mathematics & optimization |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
500 - Science |
recordtype |
marc |
publishDateSort |
2018 |
contenttype_str_mv |
txt |
container_start_page |
443 |
author_browse |
Nguyen, Dang H. Yin, George |
container_volume |
81 |
class |
510 VZ |
format_se |
Aufsätze |
author-letter |
Nguyen, Dang H. |
doi_str_mv |
10.1007/s00245-018-9504-y |
dewey-full |
510 |
title_sort |
sustainable harvesting policies under long-run average criteria: near optimality |
title_auth |
Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
abstract |
Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
abstractGer |
Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
abstract_unstemmed |
Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems. © Springer Science+Business Media, LLC, part of Springer Nature 2018 |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4027 GBV_ILN_4323 |
container_issue |
2 |
title_short |
Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
url |
https://doi.org/10.1007/s00245-018-9504-y |
remote_bool |
false |
author2 |
Yin, George |
author2Str |
Yin, George |
ppnlink |
129095184 |
mediatype_str_mv |
n |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1007/s00245-018-9504-y |
up_date |
2024-07-03T15:40:27.132Z |
_version_ |
1803572978264309760 |
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">OLC2072646251</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504131534.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2018 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00245-018-9504-y</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2072646251</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00245-018-9504-y-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="100" ind1="1" ind2=" "><subfield code="a">Nguyen, Dang H.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</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, part of Springer Nature 2018</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper develops near-optimal sustainable harvesting strategies for the predator in a predator-prey system. The objective function is of long-run average per unit time type in the path-wise sense. To date, ecological systems under environmental noise are usually modeled as stochastic differential equations driven by a Brownian motion. Recognizing that the formulation using a Brownian motion is only an idealization, in this paper, it is assumed that the environment is subject to disturbances characterized by a jump process with rapid jump rates. Under broad conditions, it is shown that the systems under consideration can be approximated by a controlled diffusion system. Based on the limit diffusion system, control policies of the original systems are constructed. Such an approach enables us to develop sustainable harvesting policies leading to near optimality. To treat the underlying problems, one of the main difficulties is due to the long-run average objective function. This in turn, requires the handling of a number of issues related to ergodicity. New approaches are developed to obtain the tightness of the underlying processes based on the population dynamic systems.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sustainability</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Near-optimal strategy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Harvesting policy</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Long-run-average control</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ergodicity</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Yin, George</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Applied mathematics & optimization</subfield><subfield code="d">Springer US, 1974</subfield><subfield code="g">81(2018), 2 vom: 28. Mai, Seite 443-478</subfield><subfield code="w">(DE-627)129095184</subfield><subfield code="w">(DE-600)7418-4</subfield><subfield code="w">(DE-576)014431300</subfield><subfield code="x">0095-4616</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:81</subfield><subfield code="g">year:2018</subfield><subfield code="g">number:2</subfield><subfield code="g">day:28</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:443-478</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00245-018-9504-y</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-OPC-MAT</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_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">81</subfield><subfield code="j">2018</subfield><subfield code="e">2</subfield><subfield code="b">28</subfield><subfield code="c">05</subfield><subfield code="h">443-478</subfield></datafield></record></collection>
|
score |
7.397253 |