Design of Oxidant Air Quality Management Strategies Using Genetic Algorithm-Based Optimization in a Decision Support System

摘要

Designing air quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable physical system models, competing design objectives, unquantifiable issues, etc. Mathematical optimization techniques offer promise in identifying low cost strategies that may be used as benchmarks or starting points for further analysis. Yet applications of optimization techniques have been lacking for some problems such as the control of tropospheric ozone that involve complex nonlinear atmospheric chemistry.