In many modeling applications, finding optimal solutions -typically in a vast and complex solution space - is a core task. This article provides an introduction to selected mathematical models and methods, which are available to address selected optimization problems. To begin with, some exemplary optimization tasks are described and approaches that have been established to solve these will be introduced. In a next step, optimization algorithms for linear and nonlinear problem formulations are briefly discussed.
The central part of the article discusses the design and application of genetic algorithms (GAs), which have been successfully applied to solve a variety of environmental and ecological modeling problems. A specific application of GAs in a multipollutant multieffect optimization framework is described in detail.
The article closes with recommendations for the development and application of optimization algorithms in ecological modeling, including selected bibliography for further reading. It needs to be stated, however, that only a brief overview is possible given the limitations in space.
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