This paper introduces a global evolutionary algorithm based on the concept of biological immune system that directly treats constraints for multi-objective engineering optimization problems. The development of optimization algorithm applied the cycle of affinity-maturation principle in the immune system that contains repeated activation, proliferation and differentiation. An enhanced expression strategy is utilized for handling constraints to improve the solution performance. The designs of Pareto front can be generated in a single simulation. All computational works completed in this paper used real-number-coded representation for genes evolution that efficiently applied on general engineering designs.
Relation:
中華民國第十三屆模糊理論及其應用會議論文集=Proceedings of 2005 the 13th National Conference on Fuzzy Theory and Its Applications，6p.
