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Optimal harvesting strategies for a multi-cycle and multi-pond shrimp operation: A practical network model

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  • Yu, Run
  • Leung, PingSun

Abstract

In this paper, we introduce a network formulation of the optimal scheduling model for a multi-cycle and multi-pond shrimp operation grounded on the original optimal harvesting theory for a single production unit. The optimal schedule comprises the harvesting and restocking time that maximizes total profit throughout the planning horizon, bounded by the underlying biological and economic conditions. The model takes into account the information such as harvest size distribution, seasonality of price, temperature and weight-dependent growth, and labor force and market demand constraints. We applied the model to an existing shrimp operation in Hawaii with 40 one-acre ponds and generated the optimal schedule for a year that maximizes overall production. The model schedule is found to be able to increase total production by 5% when compared to the schedule generated using an “educated” trial-and-error procedure currently practiced by this operation. Further insights for this multi-cycle and multi-pond scheduling problem were also generated through several alternate simulations. It is found that labor force and market demand constraints are the key factors in scheduling multi-cycle and multi-pond shrimp operations.

Suggested Citation

  • Yu, Run & Leung, PingSun, 2005. "Optimal harvesting strategies for a multi-cycle and multi-pond shrimp operation: A practical network model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(4), pages 339-354.
    • Handle: RePEc:eee:matcom:v:68:y:2005:i:4:p:339-354
    DOI: 10.1016/j.matcom.2005.01.018
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    References listed on IDEAS

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    1. PingSun Leung & Hochman, Eithan & Rowland, Lawrence W. & Wyban, James A., 1990. "Modeling shrimp production and harvesting schedules," Agricultural Systems, Elsevier, vol. 32(3), pages 233-249.
    2. Leung, PingSun & Shang, Yung C., 1989. "Modeling prawn production management system: A dynamic Markov decision approach," Agricultural Systems, Elsevier, vol. 29(1), pages 5-20.
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    4. Forsberg, Odd Inge, 1996. "Optimal stocking and harvesting of size-structured farmed fish: A multi-period linear programming approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 42(2), pages 299-305.
    5. Hean, Robyn L., 1994. "An Optimal Management Model For Intensive Aquaculture - An Application In Atlantic Salmon," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 38(1), pages 1-17, April.
    6. Robyn L. Hean, 1994. "An Optimal Management Model For Intensive Aquaculture — An Application In Atlantic Salmon," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 38(1), pages 31-47, April.
    7. Larry Karp & Arye Sadeh & Wade L. Griffin, 1986. "Cycles in Agricultural Production: The Case of Aquaculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(3), pages 553-561.
    8. Eithan Hochman & PingSun Leung & Lawrence W. Rowland & James A. Wyban, 1990. "Optimal Scheduling in Shrimp Mariculture: A Stochastic Growing Inventory Problem," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(2), pages 382-393.
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    Cited by:

    1. Peng-Sheng YOU & Yi-Chih HSIEH, 2018. "A study of production and harvesting planning for the chicken industry," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(7), pages 316-327.
    2. Yu, Run & Leung, PingSun, 2009. "Optimal harvest time in continuous aquacultural production: The case of nonhomogeneous production cycles," International Journal of Production Economics, Elsevier, vol. 117(2), pages 267-270, February.

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