TY - GEN
T1 - Stochastic fuzzy assessment for managing hydro-environmental systems under uncertainty and ambiguity
AU - Rastgoftar, Hossein
AU - Imen, Sanaz
AU - Madani, Kaveh
PY - 2012
Y1 - 2012
N2 - This paper develops a stochastic fuzzy decision making method to solve a class of decision making problems which involve simultaneous uncertainty and ambiguity when screening water resources management alternatives. In these analyses, not only the performance value with respect to a specific criterion in a given alternative is uncertain, but also the performance implications of the given alternative may be vague with respect to the considered criterion by the decision maker. The integration between Monte-Carlo simulation and fuzzy decision making may provide a unique soft computing technique linking randomness and fuzziness together. Whereas the stochastic problem is mapped into a deterministic environment through the use of a Monte-Carlo simulation process, fuzzy decision making helps entail the linguistic uncertainty (i.e., ambiguity) in decision science. With this framework, the overall performance of a wealth of alternatives can be further evaluated, resulting in considerable reduction in the uncertainty and ambiguity in the decision making arena. Practical implementation has been assessed by a case study of the Sacramento-San Joaquin Delta in California in which the performance of four water export alternatives were evaluated to determine the satisfactory solution with respect to the environmental sustainability and cost-effectiveness criteria.
AB - This paper develops a stochastic fuzzy decision making method to solve a class of decision making problems which involve simultaneous uncertainty and ambiguity when screening water resources management alternatives. In these analyses, not only the performance value with respect to a specific criterion in a given alternative is uncertain, but also the performance implications of the given alternative may be vague with respect to the considered criterion by the decision maker. The integration between Monte-Carlo simulation and fuzzy decision making may provide a unique soft computing technique linking randomness and fuzziness together. Whereas the stochastic problem is mapped into a deterministic environment through the use of a Monte-Carlo simulation process, fuzzy decision making helps entail the linguistic uncertainty (i.e., ambiguity) in decision science. With this framework, the overall performance of a wealth of alternatives can be further evaluated, resulting in considerable reduction in the uncertainty and ambiguity in the decision making arena. Practical implementation has been assessed by a case study of the Sacramento-San Joaquin Delta in California in which the performance of four water export alternatives were evaluated to determine the satisfactory solution with respect to the environmental sustainability and cost-effectiveness criteria.
UR - http://www.scopus.com/inward/record.url?scp=84866111144&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866111144&partnerID=8YFLogxK
U2 - 10.1061/9780784412312.244
DO - 10.1061/9780784412312.244
M3 - Conference contribution
AN - SCOPUS:84866111144
SN - 9780784412312
T3 - World Environmental and Water Resources Congress 2012: Crossing Boundaries, Proceedings of the 2012 Congress
SP - 2413
EP - 2421
BT - World Environmental and Water Resources Congress 2012
T2 - World Environmental and Water Resources Congress 2012: Crossing Boundaries
Y2 - 20 May 2012 through 24 May 2012
ER -