Applications of a Multi-Objective Genetic Algorithm in Chemical and Environmental Engineering


Multiobjective optimization involving simultaneous optimization of more than one objective function is quite commonly encountered in chemical and environmental engineering processes. With the implementation of stringent regulations on air and water discharge of the particulate pollutants, development of efficient fluid-solid separation devices integrating the physico-chemical processes with economic parameters is of significant commercial importance. In this chapter, multiobjective optimization using conflicting objectives such as maximization of the overall collection efficiency and minimization of both the pressure drop and the cost in commonly used fluid-particulate separation devices namely cyclone separator and venturi scrubber is illustrated using the Non-dominated Sorting Genetic Algorithm (NSGA).