Journal
JOURNAL OF ENVIRONMENTAL INFORMATICS
Volume 22, Issue 1, Pages 39-48Publisher
INT SOC ENVIRON INFORM SCI
DOI: 10.3808/jei.201300244
Keywords
fuzzy chance-constrained programming; genetic algorithm; effluent control management; agricultural system; uncertainty
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Funding
- Academic Research Fund (AcRF) Tier 1 [M4010973.030]
- Ministry of Education (MOE), Singapore
- DHI-NTU Water and Environment Research Centre and Education Hub
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A combined genetic algorithm and fuzzy simulation approach (GAFSA) was developed through integrating fuzzy chance-constrained programming (FCCP) and genetic algorithm (GA) into a general optimization framework. The major advantage of GAFSA is that it could tackle generally-shaped fuzzy membership functions on both sides of the model constraints, rather than handle single special forms like triangular or trapezoidal. An agricultural water quality management problem that has been investigated by a number of previous studies was used to demonstrate the applicability of the proposed method. The results showed that GAFSA allowed violation of system constraints at specified possibilistic confidence levels, leading to model solutions with higher system benefits. A conservative planning scheme could bring a more reliable system, but would be less economically attractive. Conversely, planning towards a higher system benefit would lead to a higher risk of system failure. The proposed model could help agricultural water managers analyse the trade-off between the overall system benefit and the failure risk of environmental compliance. A comparison of GAFSA to FCCP was given, and the potential limitations of the proposed method were also discussed.
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