Development of a Decision Support Framework forIntegrated Watershed Water Quality Management and a Generic Genetic Algorithm Based Optimizer

Abstract

The watershed management approach is a framework for addressing water quality problems at a watershed scale in an integrated manner that considers many conflicting issues including cost, environmental impact and equity in evaluating alternative control strategies. This framework enhances the capabilities of current environmental analysis frameworks by the inclusion of additional systems analytic tools such as optimization algorithms that enable efficient search for cost effective control strategies and uncertainty analysis procedures that estimate the reliability in achieving water quality targets. Traditional optimization procedures impose severe restrictions in using complex nonlinear environmental processes within a systematic search. Hence, genetic algorithms (GAs), a class of general, probabilistic, heuristic, global, search procedures, are used. Current implementation of this framework is coupled with US EPA's BASINS software system. A component of the current research is also the development of GA object classes and optimization model classes for generic use. A graphical user interface allows users to formulate mathematical programming problems and solve them using GA methodology. This set of GA object and the user interface classes together comprise the Generic Genetic Algorithm Based Optimizer (GeGAOpt), which is demonstrated through applications in solving interactively several unconstrained as well as constrained function optimization problems.Design of these systems is based on object oriented paradigm and current software engineering practices such as object oriented analysis (OOA) and object oriented design (OOD). The development follows the waterfall model for software development. The Unified Modeling Language (UML) is used for the design. The implementation is carried out using the JavaTM programming environment