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Genetic Algorithms for Optimal Operation of Soil Aquifer Treatment Systems

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  • Aihua Tang
  • Larry Mays

Abstract

The genetic algorithm (GA) is a nonconventional search technique which is patterned after the biological processes of natural selection and evolution. It has the ability to search large and complex decision spaces and handle nonconvexities. In this paper, the genetic algorithm is investigated and applied to solve the optimal operation problem of soil aquifer treatment (SAT) systems. This problem involves finding optimal water application time and drying time which maximize infiltration for a predetermined starting influent rate of waste water and subject to various physical and operational constraints. A new scaling method is developed and some improvements on the evolution procedure are presented. A comprehensive GA–SAT computer model was developed and applied to an example SAT problem. The results are encouraging, when compared with using the successive approximation linear quadratic regulator algorithm. It was found that genetic algorithms are easy to program and interface with large complicated simulators. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Aihua Tang & Larry Mays, 1998. "Genetic Algorithms for Optimal Operation of Soil Aquifer Treatment Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(5), pages 375-396, October.
    • Handle: RePEc:spr:waterr:v:12:y:1998:i:5:p:375-396
    DOI: 10.1023/A:1008030612068
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    Cited by:

    1. K. Srinivasa Raju & D. Nagesh Kumar, 2004. "Irrigation Planning using Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(2), pages 163-176, April.
    2. Hydar Ebrahimi & Reza Ghazavi & Haji Karimi, 2016. "Estimation of Groundwater Recharge from the Rainfall and Irrigation in an Arid Environment Using Inverse Modeling Approach and RS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 1939-1951, April.
    3. Huaizhi Su & Meng Yang & Zhiping Wen, 2015. "Multi-Layer Multi-Index Comprehensive Evaluation for Dike Safety," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4683-4699, October.

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