Over the past few decades there have been a growing interest in the use of biology as a source of inspiration for solving computational problems. This area of research is often referred to as Biologically Inspired Computing. The motivation of this field is primarily to extract useful metaphors from natural biological systems, in order to create effective computational solutions to complex problems in a wide range of domain areas. The concept of optimization is now well rooted as a principle underlying the analysis of many complex decision supporting system or allocation problems. It offers a certain degree of philosophical elegance that is hard to dispute, and it often offers an indispensable degree of operational simplicity. Using this optimization philosophy, one approaches a complex decision problem, involving the selection of values for a number of interrelated variables, by focusing attention on a single objective designed to quantify performance and measure the quality of the decision.