Finding a location for an air polluting facility is usually a source of heated discussions among local inhabitants and decision makers, since the effects of polluted air on human health and the environment can be quite severe.
We propose a general modeling and optimization system for the effects of a low toxic air pollutant on the inhabitants of different land-based ecosystems, including health effects on humans or other beings. Health effects are quantified on the basis of detailed cytodynamic effects in different organs and tissues. The software package OLAF (Optimal Locating Air Polluting Facilities) developed on the basis of this model does not only evaluate quantitatively the effects of a proposed decision, but uses an efficient optimization technique to optimize the location of the polluting facility with respect to the adverse effects of the pollution on the inhabitants of the modeled region.
Up to now, the decision process with respect to environmental issues and health concerns was mainly based on simulations of a small number of different decisions. However, the need for an automated optimization process incorporating detailed estimates of effects of the pollution has recently been acknowledged by the European Environmental Agency [27, 4]. Unfortunately, up to now only few attempts have been made to integrate the decision process into a general optimization procedure, thereby automatically minimizing a measure of risk. While some of the models developed with respect to this are rather simplistic [21, 20, 1], others use stochastic optimization techniques (see ,  and the references therein), methods which are known for their notoriously slow behavior.