No / A species conservation technique takes inspiration from the field of ecology, in which the population is divided into several species according to their similarity. Based on this technique, a Species Conservation Genetic Algorithms (SCGA) was established and had been proved to be very effective in finding multiple solutions of multimodal optimisation problems, including some problems known to be deceptive for genetic algorithms (GAs). In this paper, the SCGA is introduced to engineering structure design, and two structure designs are used to demonstrate the performances of the SCGA and how the choice of a meaningful measure of similarity will help in exploration of significant designs.

Yes / The need for desalinated seawater and reclaimed wastewater is increasing rapidly with the rising demands for drinkable water required for the world with continuously growing population. Reverse Osmosis (RO) processes are now among the most promising technologies used to remove chemicals from industrial effluents. N-nitrosamine compounds and especially N-nitrosodimethylamine (NDMA) are human carcinogens and can be found in industrial effluents of many industries. Particularly, NDMA is one of the by-products of disinfection process of secondary-treated wastewater effluent with chloramines, chlorines, and ozone (inhibitors). However, multi-stage RO processes with permeate reprocessing and recycling has not yet been considered for the removal of N-nitrosodimethylamine from wastewater. This research therefore, begins by investigating a number of multi-stage RO processes with permeate-reprocessing to remove N-nitrosodimethylamine (NDMA) from wastewater and finds the best configuration in terms of rejection, recovery and energy consumption via optimisation. For the first time we have applied Species Conserving Genetic Algorithm (SCGA) in optimising RO process conditions for wastewater treatment. Finally, permeate recycling is added to the best configuration and its performance is evaluated as a function of the amount of permeate being recycled via simulation. For this purpose, a mathematical model is developed based on the solution diffusion model, which is used for both optimisation and simulation. A number of model parameters have been estimated using experimental data of Fujioka et al. (Journal of Membrane Science 454 (2014) 212–219), so that the model can be used for simulation and optimisation with high accuracy and confidence.