Immune network simulations in multicriterion design

A modification to the genetic algorithm (GA) based search procedure, based on the modeling of a biological immune system, is proposed as an approach t o solving the multicriterion design problem. Such problems have received co nsiderable attention, given that decisions in engineering design practice t ypically require allocation of resources to satisfy multiple, and frequentl y conflicting requirements. The approach is particularly amenable to proble ms with a mix of continuous, discrete, and integer design variables, where the GA has been shown to perform in an effective manner. The approach consi dered in the present work is based on the concept of converting the multicr iterion problem into one with a scalar objective through the use of the uti lity function. The strength of the approach is in its ability to generate t he Pareto-Edgeworth front of compromise solutions in a single execution of the GA. A characteristic feature of biological immune systems which allows for the generation of multiple specialist antibodies, is shown to be an eff ective approach to facilitate the generation of the Pareto-Edgeworth front. Solutions to problems in structural design are presented in support of the proposed approach.