A Short Survey of Multi-objective Immune Algorithm Based on Clonal Selection

Abstract

Multi-objective immune algorithm (MOIA) is a heuristic algorithm based on artificial immune system model. Due to its characteristics of antibody clonal selection and automatic antigen recognition in the immune system, immune algorithm has become a research hotspot in the field of multi-objective optimization after the evolutionary algorithm. In this paper, the studies of multi-objective immune algorithm based on clonal selection principle are summarized and discussed. At the beginning, some background about clonal selection principle is introduced. Then, the details of each immune algorithm are expounded, which mainly include its characteristic, mechanism and drawbacks. Moreover, in order to have a visual observation of the performance of immune algorithm on solving multi-objective optimization problems, four state-of-the-art MOIAs based on clonal selection principle are tested on one widely used benchmark problem in the experimental comparison. Finally, some future research directions of MOIAs are briefly discussed.