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Scheme choice for optimal allocation of water resources based on fuzzy language evaluation and the generalized induced ordered weighted averaging operator

Author

Listed:
  • Fei Ding

    (Hiroshima University)

  • Takao Yamashita

    (Hiroshima University)

  • Han Soo Lee

    (Hiroshima University)

  • Jian-hua Ping

    (Zhengzhou University)

Abstract

The choice of scheme for the optimal allocation of water resource (OAW R) is a fuzzy multiple-attribution decision that is determined using information from many figures and fuzzy language regarding several evaluated factors, such as investment, daily water supplying, fee of contaminated water disposal, water conservation, and the development of economy. In this paper, the evaluation system employed to choose an OAWR scheme is established based on the evaluation of fuzzy language and the generalized induced ordered weighted averaging (GIOWA) operator. Considering economic aspects and a sustainable water supply, the five following constituents are chosen: 1) Investment (Yuan), 2) Daily water supply (ton/day), 3) Fee of contaminated water disposal (Yuan), 4) Water conservation (fuzzy language), and 5) Development of economy (fuzzy language). The analytic hierarchy process (AHP) method is used to determine the weighting vector. A case study on the choice of OAWR in the northern area of Shenyang city, China was conducted by a multiple-attribution decision based on the GIOWA operator. The results shows that the system employed was able to choose the best scheme of OAWR in which fuzzy and multiple-attribution decision-making should be performed.

Suggested Citation

  • Fei Ding & Takao Yamashita & Han Soo Lee & Jian-hua Ping, 2011. "Scheme choice for optimal allocation of water resources based on fuzzy language evaluation and the generalized induced ordered weighted averaging operator," Fuzzy Information and Engineering, Springer, vol. 3(2), pages 169-182, June.
    • Handle: RePEc:spr:fuzinf:v:3:y:2011:i:2:d:10.1007_s12543-011-0075-8
    DOI: 10.1007/s12543-011-0075-8
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