Waste-load allocation using genetic algorithms

This paper explores the capabilities of genetic algorithms for identifying solutions to waste-load allocation problems. Three optimization model formulations are developed for examining different waste-load allocation problems. Two of the model formulations address problems arising in the planning context while the third model addresses waste-load allocation decisions of use when developing an operational strategy for a river basin. The models can all be used to develop a trade-off relationship for a multiobjective optimization problem that would be of use to a decision maker when selecting a solution for implementation. The models developed are applied to a case study based on the Willamette River in Oregon and the resulting trade-off relationships are discussed both in objective space and in decision space.