Keywords
groundwater, monitoring, design, water resource management, multi-objective optimization, genetic algorithms
Start Date
1-7-2004 12:00 AM
Abstract
Monitoring design is a problem of paramount importance to the environmental engineering field because environmental observation data provide the sole means of assessing if engineered systems are successfully protecting human and ecologic health. The monitoring design problem is extremely challenging because it requires environmental engineers to capture an impacted system’s governing processes, elucidate human and ecologic risks, limit monitoring costs, and satisfy the interests of multiple stakeholders (e.g., site owners, regulators, and public advocates). Evolutionary multiobjective optimization (EMO) has tremendous potential to help resolve these issues by providing environmental stakeholders with a direct understanding of their monitoring tradeoffs.
Using Interactive Archives in Evolutionary Multiobjective Optimization: Case Studies for Long- Term Groundwater Monitoring Design
Monitoring design is a problem of paramount importance to the environmental engineering field because environmental observation data provide the sole means of assessing if engineered systems are successfully protecting human and ecologic health. The monitoring design problem is extremely challenging because it requires environmental engineers to capture an impacted system’s governing processes, elucidate human and ecologic risks, limit monitoring costs, and satisfy the interests of multiple stakeholders (e.g., site owners, regulators, and public advocates). Evolutionary multiobjective optimization (EMO) has tremendous potential to help resolve these issues by providing environmental stakeholders with a direct understanding of their monitoring tradeoffs.
