Solving multi-objective truss structural optimization problems considering natural frequencies of vibration and automatic member grouping

Minimizing the mass of a structure and maximizing its first natural frequency of vibration are conflicting objectives of real interest in structural design. To avoid problems with resonance, which can lead to their collapse, structures can be designed by making the first natural frequency of vibrati...

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Bibliographic Details
Published in:Evolutionary intelligence Vol. 17; no. 2; pp. 653 - 678
Main Authors: Carvalho, Érica C. R., Carvalho, José Pedro G., Bernardino, Heder S., Lemonge, Afonso C. C., Hallak, Patrícia H., Vargas, Dênis E. C.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2024
Springer Nature B.V
Subjects:
Applications of Mathematics
Artificial Intelligence
Bioinformatics
Bridges
Civil engineering
Constraints
Control
Decision making
Design
Engineering
Evolutionary computation
Genetic algorithms
Heuristic
Literature reviews
Mathematical and Computational Engineering
Mechatronics
Multiple objective analysis
Objectives
Optimization
Resonant frequencies
Review Article
Robotics
Sorting algorithms
Statistical Physics and Dynamical Systems
Structural design
Topology
Trusses
Vibration
Cardinality constraints
Multi-objective evolutionary algorithms
Natural frequencies of vibration
Multi-objective truss structural optimization
Automatic member grouping
ISSN:1864-5909, 1864-5917
Online Access:Get full text
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Summary:Minimizing the mass of a structure and maximizing its first natural frequency of vibration are conflicting objectives of real interest in structural design. To avoid problems with resonance, which can lead to their collapse, structures can be designed by making the first natural frequency of vibration high. Furthermore, it is crucial to stay away from excitation frequencies. Here we formulate and solve multi-objective structural optimization problems of trusses with these conflicting objectives. This type of problem is uncommon in the literature, since the natural frequencies of vibration are generally set as constraints rather than as objective functions. The generalized differential evolution 3 (GDE3), the nondominated sorting genetic algorithm II (NSGA-II), decision space-based niching (DN-NSGA-II), the competitive mechanism-based multi-objective particle swarm optimizer (CMOPSO), and the MOPSO with multiple search strategies (MMOPSO) are the algorithms used in this paper. Additionally, cardinality constraints are used to manage the difficulty of discovering the best member grouping, which is very effective in addressing the problems analyzed in this paper. The experiments refer to the 10-, 25-, 72-, and 200-bar trusses. Each involves two analyses, taking into account the performance indicators and the use of a multi tournament decision (MTD) method to extract the desired solutions. Furthermore, the design variables of each extracted solution, including its optimized topology, are provided.
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ISSN:1864-5909
1864-5917
DOI:10.1007/s12065-022-00804-0