Fuzzy Set Theory with Genetic Algorithm in Constrained Structural Optimization

Abstract

This paper presents a new design optimization approach which combines concepts of artificial intelligence and fuzzy logic. A genetic algorithm (GA) is the search tool. Design space is redefined through fuzzy set theory. Linear and discrete membership functions are studied to transform crisp constraints into fuzzy ones. Infeasible points are redefined as incomplete solutions by fuzzy set theory, and regarded as lower grade members of a fuzzy feasible set. Fuzzy control and adjustment are introduced to the GA's evolutionary process. An eight-bar truss optimal design (single-objective and multiobjective) is provided to explain analysis procedures of the proposed optimal method.

Department(s)

Civil, Architectural and Environmental Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 The Authors, All rights reserved.

Publication Date

01 Jan 1997

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