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Decision support system for fisheries management

Published: 04 December 2005 Publication History

Abstract

This paper presents a decision support system that is oriented toward fisheries policy and management decisions. The important current issues involve the development of an optimal harvesting plan for the fishing industry. A simulation optimization has been built to assist authorities in scheduling for a fleet of hundreds of vessels in terms of time and location of fishing, as well as amount and target species to be fished. Marine fisheries are highly complex and stochastic. A simulation model, therefore, is required. Simulation-based optimization utilizes the simulation model in obtaining the objective function values of a particular fishing schedule. A Genetic Algorithm is used as the optimization routine to determine the optimal fishing schedule, subject to fleet capacity and conservation requirements. The decision support system is then applied to the real situation in the Northeastern U.S.

References

[1]
Azadivar, F., T. Truong, K. D. E. Stokesbury, and B. J. Rothschild. 2002. Simulation based optimization in fisheries management. Proceedings of the 2002 Winter Simulation Conference, edited by E. Yücesan, C. H. Chen, J. L. Snowdon, and J. M. Charnes, 1268--1275.
[2]
Azadivar, F. 1999. Simulation optimization methodologies. Proceedings of the 1999 Winter Simulation Conference, edited by P. A. Farrington, H. B. Nembhard, D. T. Sturrock, and G. W. Evans, 93--100.
[3]
Babcock, E. A., and E. K. Pikitch. 2000. A dynamic programming model of fishing strategy choice in a multispecies trawl fishery with trip limits. Canadian Journal of Fisheries and Aquatic Sciences. 57: 357--370.
[4]
Goldberg, D. E 1989. Genetic algorithms in search, optimization and machine learning. Addison Wesley.
[5]
Michalewicz, Z., D. Dasgupta, R. G. Le Riche, and M. Schoenauer. 1996. Evolutionary algorithms for constrained engineering problems. Computers & Industrial Engineering Journal, 30 (2): 851--870.
[6]
Rothschild, B. J., J. S. Ault, and S. G. Smith. 1996. A system approach to fisheries stock assessment and management. In Stock assessment, quantitative methods and application for small scale fisheries. Edited by V. F. Gallucci, S. B. Saila, D. J. Gustafson and B. J. Rothschild. CRC press.
[7]
Ruppert, D., R. L. Reish, R. B. Deriso, and R. J. Carroll. 1984. Optimization using stochastic approximation and Monte Carlo simulation with application to harvesting of Atlantic Menhaden. Biometrics, 40: 535--545.

Cited By

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  • (2009)A decision support system for fisheries management using operations research and systems science approachExpert Systems with Applications: An International Journal10.1016/j.eswa.2008.01.08036:2(2971-2978)Online publication date: 1-Mar-2009

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cover image ACM Conferences
WSC '05: Proceedings of the 37th conference on Winter simulation
December 2005
2769 pages
ISBN:0780395190

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Winter Simulation Conference

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Published: 04 December 2005

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WSC '05 Paper Acceptance Rate 209 of 316 submissions, 66%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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  • (2009)A decision support system for fisheries management using operations research and systems science approachExpert Systems with Applications: An International Journal10.1016/j.eswa.2008.01.08036:2(2971-2978)Online publication date: 1-Mar-2009

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