A novel immune danger algorithm for constrained multiobjective optimization

A new immune optimization algorithm for constrained multiobjective optimization problems is designed based on danger theory exhibited in biological immune system. The general situation and running mechanism are presented in this paper. The algorithm identifies "dangerous" as the core idea and introduces antigen presenting cell and different danger signals. Experimental results of constrained multiobjective optimization show that the new algorithm has higher efficiency than traditional immune algorithms.