Abstract

This paper presents a constrained multiobjecthe optimzation method in the form of a robust, practical, problem-independent algorithm, and investigates the effect of multiobjective optimization on structural design. The study includes properties and characteristics of multiobjective optimization and solutions. Design objectives, constraints, and design variables as well as their effect on structural design and behavior are investigated. Fuzzy set theory is also included to construct a fuzzy constrained environment. Two new genetic algorithm operators — multiobjective fitness function and niche method -- are proposed. A new genetic algorithm process, Pareto set filter, is added to genetic algorithms. A 10-story setback building is used to illustrate the evaluation of three choices: steel frame; reinforced concrete frame; composite steel and reinforced concrete frame. Evaluation is based on economics as well as performance. Optimization goals cover weight, structural cost, and seismic energy. All three frames are subjected to the same seismic input. Constraints meet Uniform Building Code specifications and comprise stress, displacement, drift, and ratio of story stiffness. Numerical results are useful for making choices in the design process, and the new algorithms provide a powerful tool to locate a global solution.

Department(s)

Civil, Architectural and Environmental Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 American Institute of Aeronautics and Astronautics, All rights reserved.

Publication Date

01 Jan 1998

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