Journal
COMPUTERS & STRUCTURES
Volume 82, Issue 11-12, Pages 829-844Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compstruc.2004.03.003
Keywords
constrained multi-objective immune algorithm; biological immune system; multi-objective optimization; truss optimization; constrained Pareto-solutions
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An algorithm for finding constrained Pareto-optimal solutions based on the features of a biological immune system is proposed. Inter-relation ships within the constrained multi-objective immune algorithm (CMOIA) 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 were incorporated to improve the balance between exploitation and exploration. Moreover the concept of cytokines is applied for handling constraints. The effectiveness of CMOIA is evaluated through six test functions and two well-known truss sizing optimization problems. The results indicate that the CMOIA provides better performance than other methods. (C) 2004 Elsevier Ltd. All rights reserved.
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