This page has a brief overview of our research approach as well as a list of our funded projects (see menu).
Why Many-Objective Analysis?
Policy analysis and federal planning has often been based on cost benefit analysis. The approach asks, do estimates of a proposed project’s benefits outweigh the expected costs? This has led to extensive use of single-objective optimization (that is, try to maximize a benefit function).
Why look beyond cost benefit analysis?
Our group’s research advances a many-objective approach to water planning and management. We use advanced evolutionary search tools to develop tradeoffs for problem formulations that can explicitly show how conflicting objectives compare. For example, what is the cost of adding an additional unit of performance in a supply system? What is the highest level of environmental flow that can be achieved at every level of cost and reliability?
An important aspect of the approach is that trusted, full-complexity simulations are integrated into the search algorithm. It allows a rich level of detail in understanding the physical system, with all nonlinearities preserved when mapping decision maker actions to outcomes.
The search provides a number of diverse alternative designs for the system. Instead of trying to model decision makers’ preferences before the model runs are complete, we use an a posteriori approach that gives them a wealth of information to inform their selection. This is supported by interactive visualizations that provide an immersive experience where analysts can understand the implication of design decisions.