MOIA: multi-objective immune algorithm

The paper describes a novel algorithm for finding Pareto optimal solutions to multi-objective optimization problems based on the features of a biological immune system. Inter-relationships within the proposed multi-objective immune algorithm (MOIA) resemble antibody–antigen relationships in terms of specificity, germinal center, and the memory characteristics of adaptive immune responses. Gene fragment recombination and several antibody diversification schemes (including somatic recombination, somatic mutation, gene conversion, gene revision, gene drift, and nucleotide addition) were incorporated into the MOIA in order to improve the balance between exploitation and exploration. Using five performance metrics, MOIA simulation figures were compared with the data derived from a strength Pareto evolutionary algorithm (SPEA). The results indicate that the MOIA outperformed the SPEA in several areas.