A species conserving genetic algorithm for multimodal function optimization

This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.

Investigating the hydrothermal growth of zinc oxide nanostructures through seed layer control

Controlling the growth of ZnO nanostructures for photovoltaic applications will ensure greater device efficiency and parameter control. This paper reports on methods to engineer the morphology and tailor the nanostructure growth direction through the hydrothermal synthesis method. Effective control is achieved through the use of a sputtered zinc layer together with modifications of the growth solution. These nanostructures have been developed with a view to incorporation into excitonic solar cells, and methods to improve surface stability using a fully aqueous synthesis method will be discussed. © by Oldenbourg Wissenschaftsverlag, München.