Optimal placement of wastewater outfalls using an internet-based distributed computing environment and a 3D finite volume model of pollutant dispersion in offshore waters

Abstract

This chapter presents solution for a state constrained optimal control problem using an intelligent system based on evolutionary self-learning computation. The problem is solved under a parallel implementation linked to flexible evolution agent (FEA) using an Internet-based distributed computing environment. The aim of the FEA is to secure the highest benefit possible from the exploitation of the stored information, and in addition, to incorporate new procedures to facilitate internal decision-making to be automatically made in the optimization process. This chapter tries to find the optimal locations of liquid waste dumping sites in offshore waters to verify that the concentration of a considered pollutant does not exceed a pre-established limitation, either at a specific distance from the shore or in different protected areas such as fish hatcheries. The results obtained demonstrate that it is possible to use advanced evolutionary optimization tools placed on different computer platforms on the Internet to solve a real complex problem in a coordinated way.