Multi-modal topological optimization of structure using immune algorithm

Abstract In this paper the authors describe a novel approach MMIA (multi-modal immune algorithm) for finding optimal solutions to multi-modal structural problems emulating the features of a biological immune system. The use of an immune algorithm as opposed to a genetic algorithm provides this methodology with superior local search ability. Inter-relationships within the proposed algorithm 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 reversion, gene drift, and nucleotide addition) were incorporated into the MMIA in order to improve the balance between exploitation and exploration. Moreover the concept of cytokines is applied for constraint handling. Two well-studied benchmark examples in structural topology optimization problems were used to evaluate the proposed approach. The results indicate the effectiveness of MMIA.

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