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Application of fuzzy logic to multiple criteria decision making in aquacultural planning

Published:14 March 2004Publication History

ABSTRACT

The field of regional planning is characterized by the large number of issues and attributes involved, and regional planning for aquaculture development is no exception. Moreover, aquacultural plans do not have clearly defined objectives and require information that, if exist, is often imprecise and uncertain.This paper applies fuzzy set theory to multiple criteria decision making (MCDM) in aquaculture planning. In effect, the paper demonstrates how fuzzy set theory can be used to explicitly account for the inherent uncertainty encountered when planning for aquaculture development in a given region. A case study for regional aquaculture planning in Northern Egypt demonstrates the proposed fuzzy MCDM framework.

References

  1. Borges, A. R., and C. H. Antunes (2003). A fuzzy multiple objective decision support model for energy-economy planning. European Journal of Operational Research 145, 304--316.Google ScholarGoogle ScholarCross RefCross Ref
  2. Chang, N., C. G. Wen, and Y. L. Chen (1997). A fuzzy multiobjective programming approach for optimal management of the reservoir watershed. European Journal of Operational Research 99, 289--302.Google ScholarGoogle ScholarCross RefCross Ref
  3. El-Gayar, O. F., and P. S. Leung (2001). A Multiple Criteria Decision Making Framework for Regional Aquaculture Development. European Journal of Operational Research 133:462--482.Google ScholarGoogle ScholarCross RefCross Ref
  4. Fuller, R., and C. Carlsson (1996). Fuzzy multiple criteria decision making: Recent developments. Fuzzy Sets and Systems 78:139--153. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Huang, Y. F., B. W. Baetz, G. H. Huang, and L. Liu (2002). Violation analysis for solid waste management systems: an interval fuzzy programming approach. Journal of Environmental Management 65, 431--446.Google ScholarGoogle ScholarCross RefCross Ref
  6. Nash, C. E. (1995). Aquaculture Sector Planning and Management. Fishing News Books, Oxford, England.Google ScholarGoogle Scholar
  7. Rommelfanger, H. (1996). Fuzzy linear programming and applications. European Journal of Operational Research 92, 512--527.Google ScholarGoogle ScholarCross RefCross Ref
  1. Application of fuzzy logic to multiple criteria decision making in aquacultural planning

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            cover image ACM Conferences
            SAC '04: Proceedings of the 2004 ACM symposium on Applied computing
            March 2004
            1733 pages
            ISBN:1581138121
            DOI:10.1145/967900

            Copyright © 2004 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 14 March 2004

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