Remediation System Design with Multiple Uncertain Parameters Using Fuzzy Sets and Genetic Algorithm

Abstract

In this study, fuzzy sets are utilized to interpret uncertainty in aquifer parameters in the solution of groundwater optimization problems. For this purpose, an optimization model is developed for the design of groundwater remediation systems with multiple uncertain parameters and multiple candidate pumping wells. The uncertain parameters selected include hydraulic conductivity and longitudinal and transverse dispersion coefficients. A genetic algorithm embedded with fuzzy vertex algebra is used to solve the optimization model. This approach is an extension of an earlier method proposed by the writers that is more suitable for large scale applications with multiple uncertain parameters. The numerical experiments are conducted to demonstrate the effectiveness of the procedures discussed in this study. The approach presented in this study provides guidance for the interpretation of uncertain parameters in groundwater optimization problems using fuzzy sets. The computational results show that the combined use of genetic algorithms and fuzzy vertex analysis yields an efficient method for the solution of optimization problems with multiple uncertain aquifer parameters.