ABSTRACT
Biomimetics is the „eld of science and engineering that seeks to understand and to use nature as a model for copying, adapting, and inspiring concepts and designs. Evolution led to effective solutions to nature’s challenges, which were improved over millions of years. Humans have always made efforts to use nature as a model for innovation and problem solving. These efforts have become more intensive in recent years; systematic studies of nature are being made toward better understanding of nature’s capabilities and for applying more sophisticated capabilities in various „elds (Benyus, 1998; Vincent, 2001; Bar-Cohen, 2005). As part of the „eld of biomimetics, scientists are seeking rules, concepts, mechanisms, and principles of biology to inspire new engineering possibilities, including manufacturing, mechanisms, materials, processes, and algorithms. Some of the bene„ts that resulted are improved structures, actuators, sensors, interfaces, control, software, drugs, defense, intelligence, and many others. A genetic algorithm is an example of a biologically inspired algorithm-it mimics the survival of the „ttest, and it is widely used for optimization of mathematical functions (Drezner and Drezner, 2005; Lipson, 2005). Modeling for optimization includes activities in ant colonies and pigeons’ seed-picking process. The latter is also known as the particle swarm optimization algorithm, and it is based on the statistical process of seed picking. This algorithm is very effective in evolving hardware, particularly in designing combinational electric circuits (Amaral et al., 2004). Other applications of this algorithm include routing vehicle and telecommunication networks.
