MATLAB Implementation of Artificial Immune Algorithm with Code Description

In this article, I would like to introduce a fascinating computational program - the Artificial Immune Algorithm implementation. This program is designed based on the working principles of the human immune system, incorporating key mechanisms such as antigen recognition, antibody generation, and immune memory. The MATLAB implementation typically includes core functions like population initialization, affinity calculation, clonal selection, and mutation operations. Through this program, we can better understand the operation of human immune systems while applying these biological principles to solve various problems in computer science. Notably, the Artificial Immune Algorithm demonstrates significant potential in optimization problems, as it can self-adaptively adjust algorithm parameters through mechanisms like antibody diversity maintenance and hypermutation to find optimal solutions. The code structure usually involves main components: antigen representation (problem formulation), antibody population (solution candidates), affinity evaluation (fitness function), and immune operations (cloning and mutation). If you're interested in computer science or optimization algorithms, I recommend paying attention to this program, as it may become an important research direction in future computer science fields. Thank you for reading!