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
Gespeichert in:
| Autor*in: |
Nguyen, Dang H. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Applied mathematics & optimization - Springer US, 1974, 81(2018), 2 vom: 28. Mai, Seite 443-478 |
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| Übergeordnetes Werk: |
volume:81 ; year:2018 ; number:2 ; day:28 ; month:05 ; pages:443-478 |
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| DOI / URN: |
10.1007/s00245-018-9504-y |
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| 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. | ||
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| 650 | 4 | |a Long-run-average control | |
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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 |
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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 |
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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 |
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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 |
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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 |
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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 |
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Sustainable Harvesting Policies Under Long-Run Average Criteria: Near Optimality |
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