Abstract

One of the first steps in developing an optimal water resources design model is creating appropriate objective functions that represent the primary goals of the design. In many cases, one major objective is minimizing cost. A more realistic cost function, with detailed cost terms, may yield more accurate results but will require more development effort. This research examines the benefits of developing a realistic cost function using two multiobjective groundwater remediation case studies. The results show that realistic cost functions find better solutions than the simplified cost functions, as well as identifying more optimal solutions on the Pareto frontier than the other functions. The realistic cost functions achieved up to 14% improvement in total cost, although the degree of loss in accuracy varies substantially for the two case studies considered in this work and for different parameter settings within each case study. Given the difficulties of predicting which case studies or parameter settings would have significant loss of performance from using simplified cost functions, investments in developing accurate site-specific cost functions appear to be worthwhile.

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