Abstract
Contemporary heuristic search procedures [e.g., evolutionary algorithms (EAs)] continue to offer increased capabilities for systematic search for a range of water resources and environmental management problems. These problems are often riddled, however, with numerous unquantifiable issues that are important when making decisions, but escape being incorporated in the system model. The mathematically optimal solution to such an incompletely defined model may be found unrealistic or altogether incorrect for the real problem. Optimization procedures could still be made useful if they can be utilized effectively to generate, in addition to the optimal solution, a small number of different alternatives that are near optimal. Alternatives with maximal differences in the decision variable values are expected to perform differently with respect to the unmodeled issues, providing valuable choices when making decisions. Although successful alternative generation procedures have been reported for mathematical progra...
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