The complexity of municipal water supply planning is increasing significantly due to climate change, infrastructure vulnerability, demand uncertainty, and changing social values. This complexity and uncertainty requires a robust framework for planning and decision making, in which a multitude of future situations and potential solutions can be evaluated simultaneously based on different objectives while accounting for the associated uncertainty. Generally, this can be referred to as Robust Decision Making (RDM). There is growing interest in using Multi-Objective Evolutionary Algorithms (MOEA) as a tool in a RDM process to help assess complex system tradeoffs for water utility planning.
Using existing models and data from four utilities, this study will investigate how different problem formulations might impact planning decisions in real world planning settings for utilities. The ultimate goal is to develop a compendium of case studies describing the different water systems, planning challenges, and how the MOEA tools were used to help analyze those tradeoffs. Tailored Collaboration partners: Colorado Springs Utilities, Tarrant Regional Water District, Tampa Bay Water, and Melbourne Water Corporation.