IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v37y1989i2p240-254.html
   My bibliography  Save this article

A Partially Observable Model of Decision Making by Fishermen

Author

Listed:
  • Daniel E. Lane

    (University of Ottawa, Ottawa, Ontario, Canada)

Abstract

This paper presents an application of a partially observable Markov decision process for the intraseasonal decisions of fishing vessel operators. Throughout each fishing season, independent vessel operators must decide in which zone or fishing ground of the fishery to fish during each period to catch the most fish with the highest return to fishing effort. Fishermen's decisions are assumed to be made to maximize net operating income. The decision model incorporates the potential fish catch, the cost of the fishing effort, and the unit price of fish. Catch potential is modeled by considering the abundance of the fish stock and the catchability of the fishing technique. Abundance dynamics not observed directly are modeled as a Markov chain with a parsimonious state-space representation, which renders the problem practicable. Dynamic decision policies are computed by the method of optimal control of the process over a finite horizon. The resultant policies are used to simulate distributions of fishermen's net operating income, fishing effort dynamics, and catch statistics. The model may be used as a decision aid in the regulation of the common property fisheries resource.

Suggested Citation

  • Daniel E. Lane, 1989. "A Partially Observable Model of Decision Making by Fishermen," Operations Research, INFORMS, vol. 37(2), pages 240-254, April.
    • Handle: RePEc:inm:oropre:v:37:y:1989:i:2:p:240-254
    DOI: 10.1287/opre.37.2.240
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.37.2.240
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.37.2.240?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Givon, Moshe & Grosfeld-Nir, Abraham, 2008. "Using partially observed Markov processes to select optimal termination time of TV shows," Omega, Elsevier, vol. 36(3), pages 477-485, June.
    2. Hao Zhang, 2010. "Partially Observable Markov Decision Processes: A Geometric Technique and Analysis," Operations Research, INFORMS, vol. 58(1), pages 214-228, February.
    3. Kvamsdal, Sturla F. & Maroto, José M. & Morán, Manuel & Sandal, Leif K., 2020. "Bioeconomic modeling of seasonal fisheries," European Journal of Operational Research, Elsevier, vol. 281(2), pages 332-340.
    4. Shoshana Anily & Abraham Grosfeld-Nir, 2006. "An Optimal Lot-Sizing and Offline Inspection Policy in the Case of Nonrigid Demand," Operations Research, INFORMS, vol. 54(2), pages 311-323, April.
    5. Williams, Byron K., 2009. "Markov decision processes in natural resources management: Observability and uncertainty," Ecological Modelling, Elsevier, vol. 220(6), pages 830-840.
    6. Chernonog, Tatyana & Avinadav, Tal, 2016. "A two-state partially observable Markov decision process with three actionsAuthor-Name: Ben-Zvi, Tal," European Journal of Operational Research, Elsevier, vol. 254(3), pages 957-967.
    7. Williams, Byron K., 2011. "Resolving structural uncertainty in natural resources management using POMDP approaches," Ecological Modelling, Elsevier, vol. 222(5), pages 1092-1102.
    8. Abraham Grosfeld‐Nir & Eyal Cohen & Yigal Gerchak, 2007. "Production to order and off‐line inspection when the production process is partially observable," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(8), pages 845-858, December.
    9. Fackler, Paul L. & Haight, Robert G., 2014. "Monitoring as a partially observable decision problem," Resource and Energy Economics, Elsevier, vol. 37(C), pages 226-241.
    10. Bjorndal, Trond & Lane, Daniel E. & Weintraub, Andres, 2004. "Operational research models and the management of fisheries and aquaculture: A review," European Journal of Operational Research, Elsevier, vol. 156(3), pages 533-540, August.
    11. Ives, M.C. & Scandol, J.P. & Greenville, J., 2013. "A bio-economic management strategy evaluation for a multi-species, multi-fleet fishery facing a world of uncertainty," Ecological Modelling, Elsevier, vol. 256(C), pages 69-84.
    12. Grosfeld-Nir, Abraham, 2007. "Control limits for two-state partially observable Markov decision processes," European Journal of Operational Research, Elsevier, vol. 182(1), pages 300-304, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:oropre:v:37:y:1989:i:2:p:240-254. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.