Multi-objective optimal design of truss structure with immune algorithm

An algorithm for finding constrained Pareto-optimal solutions based on the features of a biological immune system is proposed. Inter-relationships within the constrained multi-objective immune algorithm (CMOIA) resemble antibody–antigen relationships in terms of specificity, germinal center, and the...

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Bibliographic Details
Published in:	Computers & structures Vol. 82; no. 11; pp. 829 - 844
Main Authors:	Luh, Guan-Chun, Chueh, Chung-Huei
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.05.2004
Subjects:	Biological immune system Constrained multi-objective immune algorithm Constrained Pareto-solutions Multi-objective optimization, truss optimization Biological immune system Constrained multi-objective immune algorithm Multi-objective optimization, truss optimization Constrained Pareto-solutions
ISSN:	0045-7949, 1879-2243
Online Access:	Get full text
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Summary:	An algorithm for finding constrained Pareto-optimal solutions based on the features of a biological immune system is proposed. Inter-relationships 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.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0045-7949 1879-2243
DOI:	10.1016/j.compstruc.2004.03.003