Artificial Immune Algorithm

The Artificial Immune Algorithm is a computational optimization technique suitable for solving both single-objective and multi-objective optimization problems. Inspired by biological immune system mechanisms, this algorithm implements optimization through key immunological concepts including immune element introduction, antibody cloning, and antibody mutation. These mechanisms enable effective exploration and optimization of complex problem spaces through population-based evolutionary operations. Implementation typically involves initializing antibody populations, calculating affinity values using fitness functions, performing clonal selection based on affinity, and introducing diversity through hypermutation operators. The algorithm demonstrates strong performance in practical applications and is widely used for solving various complex optimization problems across engineering domains, featuring robust global search capabilities and effective constraint handling through its immunological inspiration.